Partial Least Square Analyses of Landscape and Surface Water Biota Associations in the Savannah River Basin

EPA Science Inventory

Ecologists are often faced with problem of small sample size, correlated and large number of predictors, and high noise-to-signal relationships. This necessitates excluding important variables from the model when applying standard multiple or multivariate regression analyses. In ...

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Physical Activity and Depressive Symptoms in Four Ethnic Groups of Midlife Women

PubMed Central

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2014-01-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic-groups of midlife women in the U.S. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women; and the Kaiser Physical Activity Survey. The data were analyzed using chi-square tests, the ANOVA, twoway ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. PMID:24879749

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

The chi-square test of independence.

PubMed

McHugh, Mary L

2013-01-01

The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others. The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer's V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer's V to produce relative low correlation measures, even for highly significant results.

Predicting falls in older adults using the four square step test.

PubMed

Cleary, Kimberly; Skornyakov, Elena

2017-10-01

The Four Square Step Test (FSST) is a performance-based balance tool involving stepping over four single-point canes placed on the floor in a cross configuration. The purpose of this study was to evaluate properties of the FSST in older adults who lived independently. Forty-five community dwelling older adults provided fall history and completed the FSST, Berg Balance Scale (BBS), Timed Up and Go (TUG), and Tinetti in random order. Future falls were recorded for 12 months following testing. The FSST accurately distinguished between non-fallers and multiple fallers, and the 15-second threshold score accurately distinguished multiple fallers from non-multiple fallers based on fall history. The FSST predicted future falls, and performance on the FSST was significantly correlated with performance on the BBS, TUG, and Tinetti. However, the test is not appropriate for older adults who use walkers. Overall, the FSST is a valid yet underutilized measure of balance performance and fall prediction tool that physical therapists should consider using in ambulatory community dwelling older adults.

Physical activity and depressive symptoms in four ethnic groups of midlife women.

PubMed

Im, Eun-Ok; Ham, Ok Kyung; Chee, Eunice; Chee, Wonshik

2015-06-01

The purpose of this study was to determine the associations between physical activity and depression and the multiple contextual factors influencing these associations in four major ethnic groups of midlife women in the United States. This was a secondary analysis of the data from 542 midlife women. The instruments included questions on background characteristics and health and menopausal status; the Depression Index for Midlife Women (DIMW); and the Kaiser Physical Activity Survey (KPAS). The data were analyzed using chi-square tests, the ANOVA, two-way ANOVA, correlation analyses, and hierarchical multiple regression analyses. The women's depressive symptoms were negatively correlated with active living and sports/exercise physical activities whereas they were positively correlated with occupational physical activities (p < .01). Family income was the strongest predictor of their depressive symptoms. Increasing physical activity may improve midlife women's depressive symptoms, but the types of physical activity and multiple contextual factors need to be considered in intervention development. © The Author(s) 2014.

Digital transceiver design for two-way AF-MIMO relay systems with imperfect CSI

NASA Astrophysics Data System (ADS)

Hu, Chia-Chang; Chou, Yu-Fei; Chen, Kui-He

2013-09-01

In the paper, combined optimization of the terminal precoders/equalizers and single-relay precoder is proposed for an amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-way single-relay system with correlated channel uncertainties. Both terminal transceivers and relay precoding matrix are designed based on the minimum mean square error (MMSE) criterion when terminals are unable to erase completely self-interference due to imperfect correlated channel state information (CSI). This robust joint optimization problem of beamforming and precoding matrices under power constraints belongs to neither concave nor convex so that a nonlinear matrix-form conjugate gradient (MCG) algorithm is applied to explore local optimal solutions. Simulation results show that the robust transceiver design is able to overcome effectively the loss of bit-error-rate (BER) due to inclusion of correlated channel uncertainties and residual self-interference.

An Improved Weighted Partial Least Squares Method Coupled with Near Infrared Spectroscopy for Rapid Determination of Multiple Components and Anti-Oxidant Activity of Pu-Erh Tea.

PubMed

Liu, Ze; Xie, Hua-Lin; Chen, Lin; Huang, Jian-Hua

2018-05-02

Background: Pu-erh tea is a unique microbially fermented tea, which distinctive chemical constituents and activities are worthy of systematic study. Near infrared spectroscopy (NIR) coupled with suitable chemometrics approaches can rapidly and accurately quantitatively analyze multiple compounds in samples. Methods: In this study, an improved weighted partial least squares (PLS) algorithm combined with near infrared spectroscopy (NIR) was used to construct a fast calibration model for determining four main components, i.e., tea polyphenols, tea polysaccharide, total flavonoids, theanine content, and further determine the total antioxidant capacity of pu-erh tea. Results: The final correlation coefficients R square for tea polyphenols, tea polysaccharide, total flavonoids content, theanine content, and total antioxidant capacity were 0.8288, 0.8403, 0.8415, 0.8537 and 0.8682, respectively. Conclusions : The current study provided a comprehensive study of four main ingredients and activity of pu-erh tea, and demonstrated that NIR spectroscopy technology coupled with multivariate calibration analysis could be successfully applied to pu-erh tea quality assessment.

Prediction of Therapy Tumor-Absorbed Dose Estimates in I-131 Radioimmunotherapy Using Tracer Data Via a Mixed-Model Fit to Time Activity

PubMed Central

Koral, Kenneth F.; Avram, Anca M.; Kaminski, Mark S.; Dewaraja, Yuni K.

2012-01-01

Abstract Background For individualized treatment planning in radioimmunotherapy (RIT), correlations must be established between tracer-predicted and therapy-delivered absorbed doses. The focus of this work was to investigate this correlation for tumors. Methods The study analyzed 57 tumors in 19 follicular lymphoma patients treated with I-131 tositumomab and imaged with SPECT/CT multiple times after tracer and therapy administrations. Instead of the typical least-squares fit to a single tumor's measured time-activity data, estimation was accomplished via a biexponential mixed model in which the curves from multiple subjects were jointly estimated. The tumor-absorbed dose estimates were determined by patient-specific Monte Carlo calculation. Results The mixed model gave realistic tumor time-activity fits that showed the expected uptake and clearance phases even with noisy data or missing time points. Correlation between tracer and therapy tumor-residence times (r=0.98; p<0.0001) and correlation between tracer-predicted and therapy-delivered mean tumor-absorbed doses (r=0.86; p<0.0001) were very high. The predicted and delivered absorbed doses were within±25% (or within±75 cGy) for 80% of tumors. Conclusions The mixed-model approach is feasible for fitting tumor time-activity data in RIT treatment planning when individual least-squares fitting is not possible due to inadequate sampling points. The good correlation between predicted and delivered tumor doses demonstrates the potential of using a pretherapy tracer study for tumor dosimetry-based treatment planning in RIT. PMID:22947086

Least squares reverse time migration of controlled order multiples

NASA Astrophysics Data System (ADS)

Liu, Y.

2016-12-01

Imaging using the reverse time migration of multiples generates inherent crosstalk artifacts due to the interference among different order multiples. Traditionally, least-square fitting has been used to address this issue by seeking the best objective function to measure the amplitude differences between the predicted and observed data. We have developed an alternative objective function by decomposing multiples into different orders to minimize the difference between Born modeling predicted multiples and specific-order multiples from observational data in order to attenuate the crosstalk. This method is denoted as the least-squares reverse time migration of controlled order multiples (LSRTM-CM). Our numerical examples demonstrated that the LSRTM-CM can significantly improve image quality compared with reverse time migration of multiples and least-square reverse time migration of multiples. Acknowledgments This research was funded by the National Nature Science Foundation of China (Grant Nos. 41430321 and 41374138).

Incident Energy Dependence of p t Correlations at RHIC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, J.; Aggarwal, M. M.; Ahammed, Z.

2005-10-01

We present results for two-particle transverse momentum correlations, Δp t,iΔ t,j, as a function of event centrality for Au+Au collisions at √( sNN) = 20, 62, 130, and 200 GeV at the Relativistic Heavy Ion Collider. We observe correlations decreasing with centrality that are similar at all four incident energies. The correlations multiplied by the multiplicity density increase with incident energy and the centrality dependence may show evidence of processes such as thermalization, jet production, or the saturation of transverse flow. The square root of the correlations divided by the event-wise average transverse momentum per event shows little or nomore » beam energy dependence and generally agrees with previous measurements at the Super Proton Synchrotron.« less

MC3: Multi-core Markov-chain Monte Carlo code

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan

2016-10-01

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

Liquid detection with InGaAsP semiconductor lasers having multiple short external cavities.

PubMed

Zhu, X; Cassidy, D T

1996-08-20

A liquid detection system consisting of a diode laser with multiple short external cavities (MSXC's) is reported. The MSXC diode laser operates single mode on one of 18 distinct modes that span a range of 72 nm. We selected the modes by setting the length of one of the external cavities using a piezoelectric positioner. One can measure the transmission through cells by modulating the injection current at audio frequencies and using phase-sensitive detection to reject the ambient light and reduce 1/f noise. A method to determine regions of single-mode operation by the rms of the output of the laser is described. The transmission data were processed by multivariate calibration techniques, i.e., partial least squares and principal component regression. Water concentration in acetone was used to demonstrate the performance of the system. A correlation coefficient of R(2) = 0.997 and 0.29% root-mean-square error of prediction are found for water concentration over the range of 2-19%.

An integrated, ethically driven environmental model of clinical decision making in emergency settings.

PubMed

Wolf, Lisa

2013-02-01

To explore the relationship between multiple variables within a model of critical thinking and moral reasoning. A quantitative descriptive correlational design using a purposive sample of 200 emergency nurses. Measured variables were accuracy in clinical decision-making, moral reasoning, perceived care environment, and demographics. Analysis was by bivariate correlation using Pearson's product-moment correlation coefficients, chi square and multiple linear regression analysis. The elements as identified in the integrated ethically-driven environmental model of clinical decision-making (IEDEM-CD) corrected depict moral reasoning and environment of care as factors significantly affecting accuracy in decision-making. The integrated, ethically driven environmental model of clinical decision making is a framework useful for predicting clinical decision making accuracy for emergency nurses in practice, with further implications in education, research and policy. A diagnostic and therapeutic framework for identifying and remediating individual and environmental challenges to accurate clinical decision making. © 2012, The Author. International Journal of Nursing Knowledge © 2012, NANDA International.

Ex-vivo UV autofluorescence imaging and fluorescence spectroscopy of atherosclerotic pathology in human aorta

NASA Astrophysics Data System (ADS)

Lewis, William; Williams, Maura; Franco, Walfre

2017-02-01

The aim of our study was to identify fluorescence excitation-emission pairs correlated with atherosclerotic pathology in ex-vivo human aorta. Wide-field images of atherosclerotic human aorta were captured using UV and visible excitation and emission wavelength pairs of several known fluorophores to investigate correspondence with gross pathologic features. Fluorescence spectroscopy and histology were performed on 21 aortic samples. A matrix of Pearson correlation coefficients were determined for the relationship between relevant histologic features and the intensity of emission for 427 wavelength pairs. A multiple linear regression analysis indicated that elastin (370/460 nm) and tryptophan (290/340 nm) fluorescence predicted 58% of the variance in intima thickness (R-squared = 0.588, F(2,18) = 12.8, p=.0003), and 48% of the variance in media thickness (R-squared = 0.483, F(2,18) = 8.42, p=.002), suggesting that endogenous fluorescence intensity at these wavelengths can be utilized for improved pathologic characterization of atherosclerotic plaques.

Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys.

PubMed

Jalili, Majid; Nazem, Farzad; Sazvar, Akbar; Ranjbar, Kamal

2018-05-14

To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m ) - (0.732 × body mass index kg/m2 ) (R 2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R 2 p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings. Copyright © 2018 Elsevier Inc. All rights reserved.

40 CFR Appendix C to Subpart Nnn... - Method for the Determination of Product Density

Code of Federal Regulations, 2011 CFR

2011-07-01

... insulation. The method is applicable to all cured board and blanket products. 2. Equipment One square foot (12 in. by 12 in.) template, or templates that are multiples of one square foot, for use in cutting... procedure for the designated product. 3.2Cut samples using one square foot (or multiples of one square foot...

40 CFR Appendix C to Subpart Nnn... - Method for the Determination of Product Density

Code of Federal Regulations, 2012 CFR

2012-07-01

.... The method is applicable to all cured board and blanket products. 2. Equipment One square foot (12 in. by 12 in.) template, or templates that are multiples of one square foot, for use in cutting... procedure for the designated product. 3.2Cut samples using one square foot (or multiples of one square foot...

40 CFR Appendix C to Subpart Nnn... - Method for the Determination of Product Density

Code of Federal Regulations, 2010 CFR

2010-07-01

.... The method is applicable to all cured board and blanket products. 2. Equipment One square foot (12 in. by 12 in.) template, or templates that are multiples of one square foot, for use in cutting... procedure for the designated product. 3.2Cut samples using one square foot (or multiples of one square foot...

Cognitive Code-Division Channelization

DTIC Science & Technology

2011-04-01

22] G. N. Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA binary signature sets,” IEEE Trans...Commun., vol. 51, pp. 48-51, Jan. 2003. [23] C. Ding, M. Golin, and T. Klve, “Meeting the Welch and Karystinos- Pados bounds on DS - CDMA binary...receiver pair coexisting with a primary code-division multiple-access ( CDMA ) system. Our objective is to find the optimum transmitting power and code

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Absolute binding free energies between T4 lysozyme and 141 small molecules: calculations based on multiple rigid receptor configurations

PubMed Central

Xie, Bing; Nguyen, Trung Hai; Minh, David D. L.

2017-01-01

We demonstrate the feasibility of estimating protein-ligand binding free energies using multiple rigid receptor configurations. Based on T4 lysozyme snapshots extracted from six alchemical binding free energy calculations with a flexible receptor, binding free energies were estimated for a total of 141 ligands. For 24 ligands, the calculations reproduced flexible-receptor estimates with a correlation coefficient of 0.90 and a root mean square error of 1.59 kcal/mol. The accuracy of calculations based on Poisson-Boltzmann/Surface Area implicit solvent was comparable to previously reported free energy calculations. PMID:28430432

40 CFR Appendix C to Subpart Nnn... - Method for the Determination of Product Density

Code of Federal Regulations, 2013 CFR

2013-07-01

... One square foot (12 in. by 12 in.) template, or templates that are multiples of one square foot, for... to the plant's written procedure for the designated product. 3.2Cut samples using one square foot (or multiples of one square foot) template. 3.3Weigh product and obtain area weight (lb/ft2). 3.4Measure sample...

40 CFR Appendix C to Subpart Nnn... - Method for the Determination of Product Density

Code of Federal Regulations, 2014 CFR

2014-07-01

... One square foot (12 in. by 12 in.) template, or templates that are multiples of one square foot, for... to the plant's written procedure for the designated product. 3.2Cut samples using one square foot (or multiples of one square foot) template. 3.3Weigh product and obtain area weight (lb/ft2). 3.4Measure sample...

Time-frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes

NASA Astrophysics Data System (ADS)

Abid, Fathi; Kaffel, Bilel

2018-01-01

Understanding the interrelationships of the global macro assets is crucial for global macro investing. This paper investigates the local variance and the interconnection between the stock, gold, oil, Forex and the implied volatility markets in the time/frequency domains using the wavelet methodology, including the wavelet power spectrum, the wavelet squared coherence and phase difference, the wavelet multiple correlation and cross-correlation. The univariate analysis reveals that, in some crisis periods, underlying asset markets present the same pattern in terms of the wavelet power spectrum indicating high volatility for the medium scale, and that for the other market stress periods, volatility behaves differently. Moreover, unlike the underlying asset markets, the implied volatility markets are characterized by high power regions across the entire period, even in the absence of economic events. Bivariate results show a bidirectional relationship between the underlying assets and their corresponding implied volatility indexes, and a steady co-movement between the stock index and its corresponding fear index. Multiple correlation analysis indicates a strong correlation between markets at high scales with evidence of a nearly perfect integration for a period longer than a year. In addition, the hedging strategies based on the volatility index lead to an increase in portfolio correlation. On the other hand, the results from multiple cross-correlations reveal that the lead-lag effect starts from the medium scale and that the VIX (stock market volatility index) index is the potential leader or follower of the other markets.

Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao Yongni; He Yong; Mao Jingyuan

Visible and near-infrared (Vis/NIR) reflectance spectroscopy has been investigated for its ability to nondestructively detect acidity in bayberry juice. What we believe to be a new, better mathematic model is put forward, which we have named principal component analysis-stepwise regression analysis-backpropagation neural network (PCA-SRA-BPNN), to build a correlation between the spectral reflectivity data and the acidity of bayberry juice. In this model, the optimum network parameters,such as the number of input nodes, hidden nodes, learning rate, and momentum, are chosen by the value of root-mean-square (rms) error. The results show that its prediction statistical parameters are correlation coefficient (r) ofmore » 0.9451 and root-mean-square error of prediction(RMSEP) of 0.1168. Partial least-squares (PLS) regression is also established to compare with this model. Before doing this, the influences of various spectral pretreatments (standard normal variate, multiplicative scatter correction, S. Golay first derivative, and wavelet package transform) are compared. The PLS approach with wavelet package transform preprocessing spectra is found to provide the best results, and its prediction statistical parameters are correlation coefficient (r) of 0.9061 and RMSEP of 0.1564. Hence, these two models are both desirable to analyze the data from Vis/NIR spectroscopy and to solve the problem of the acidity prediction of bayberry juice. This supplies basal research to ultimately realize the online measurements of the juice's internal quality through this Vis/NIR spectroscopy technique.« less

[Based on the LS-SVM modeling method determination of soil available N and available K by using near-infrared spectroscopy].

PubMed

Liu, Xue-Mei; Liu, Jian-She

2012-11-01

Visible infrared spectroscopy (Vis/SW-NIRS) was investigated in the present study for measurement accuracy of soil properties,namely, available nitrogen(N) and available potassium(K). Three types of pretreatments including standard normal variate (SNV), multiplicative scattering correction (MSC) and Savitzky-Golay smoothing+first derivative were adopted to eliminate the system noises and external disturbances. Then partial least squares (PLS) and least squares-support vector machine (LS-SVM) models analysis were implemented for calibration models. Simultaneously, the performance of least squares-support vector machine (LS-SVM) models was compared with three kinds of inputs, including PCA(PCs), latent variables (LVs), and effective wavelengths (EWs). The results indicated that all LS-SVM models outperformed PLS models. The performance of the model was evaluated by the correlation coefficient (r2) and RMSEP. The optimal EWs-LS-SVM models were achieved, and the correlation coefficient (r2) and RMSEP were 0.82 and 17.2 for N and 0.72 and 15.0 for K, respectively. The results indicated that visible and short wave-near infrared spectroscopy (Vis/SW-NIRS)(325-1 075 nm) combined with LS-SVM could be utilized as a precision method for the determination of soil properties.

Attenuation of the Squared Canonical Correlation Coefficient under Varying Estimates of Score Reliability

ERIC Educational Resources Information Center

Wilson, Celia M.

2010-01-01

Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…

The 7-item generalized anxiety disorder scale as a tool for measuring generalized anxiety in multiple sclerosis.

PubMed

Terrill, Alexandra L; Hartoonian, Narineh; Beier, Meghan; Salem, Rana; Alschuler, Kevin

2015-01-01

Generalized anxiety disorder (GAD) is common in multiple sclerosis (MS) but understudied. Reliable and valid measures are needed to advance clinical care and expand research in this area. The objectives of this study were to examine the psychometric properties of the 7-item Generalized Anxiety Disorder Scale (GAD-7) in individuals with MS and to analyze correlates of GAD. Participants (N = 513) completed the anxiety module of the Patient Health Questionnaire (GAD-7). To evaluate psychometric properties of the GAD-7, the sample was randomly split to conduct exploratory and confirmatory factor analyses. Based on the exploratory factor analysis, a one-factor structure was specified for the confirmatory factor analysis, which showed excellent global fit to the data (χ(2) 12 = 15.17, P = .23, comparative fit index = 0.99, root mean square error of approximation = 0.03, standardized root mean square residual = 0.03). The Cronbach alpha (0.75) indicated acceptable internal consistency for the scale. Furthermore, the GAD-7 was highly correlated with the Hospital Anxiety and Depression Scale-Anxiety (r = 0.70). Age and duration of MS were both negatively associated with GAD. Higher GAD-7 scores were observed in women and individuals with secondary progressive MS. Individuals with higher GAD-7 scores also endorsed more depressive symptoms. These findings support the reliability and internal validity of the GAD-7 for use in MS. Correlational analyses revealed important relationships with demographics, disease course, and depressive symptoms, which suggest the need for further anxiety research.

The 7-Item Generalized Anxiety Disorder Scale as a Tool for Measuring Generalized Anxiety in Multiple Sclerosis

PubMed Central

Hartoonian, Narineh; Beier, Meghan; Salem, Rana; Alschuler, Kevin

2015-01-01

Background: Generalized anxiety disorder (GAD) is common in multiple sclerosis (MS) but understudied. Reliable and valid measures are needed to advance clinical care and expand research in this area. The objectives of this study were to examine the psychometric properties of the 7-item Generalized Anxiety Disorder Scale (GAD-7) in individuals with MS and to analyze correlates of GAD. Methods: Participants (N = 513) completed the anxiety module of the Patient Health Questionnaire (GAD-7). To evaluate psychometric properties of the GAD-7, the sample was randomly split to conduct exploratory and confirmatory factor analyses. Results: Based on the exploratory factor analysis, a one-factor structure was specified for the confirmatory factor analysis, which showed excellent global fit to the data (χ212 = 15.17, P = .23, comparative fit index = 0.99, root mean square error of approximation = 0.03, standardized root mean square residual = 0.03). The Cronbach alpha (0.75) indicated acceptable internal consistency for the scale. Furthermore, the GAD-7 was highly correlated with the Hospital Anxiety and Depression Scale–Anxiety (r = 0.70). Age and duration of MS were both negatively associated with GAD. Higher GAD-7 scores were observed in women and individuals with secondary progressive MS. Individuals with higher GAD-7 scores also endorsed more depressive symptoms. Conclusions: These findings support the reliability and internal validity of the GAD-7 for use in MS. Correlational analyses revealed important relationships with demographics, disease course, and depressive symptoms, which suggest the need for further anxiety research. PMID:25892974

Multifractal analysis of time series generated by discrete Ito equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telesca, Luciano; Czechowski, Zbigniew; Lovallo, Michele

2015-06-15

In this study, we show that discrete Ito equations with short-tail Gaussian marginal distribution function generate multifractal time series. The multifractality is due to the nonlinear correlations, which are hidden in Markov processes and are generated by the interrelation between the drift and the multiplicative stochastic forces in the Ito equation. A link between the range of the generalized Hurst exponents and the mean of the squares of all averaged net forces is suggested.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Least squares regression methods for clustered ROC data with discrete covariates.

PubMed

Tang, Liansheng Larry; Zhang, Wei; Li, Qizhai; Ye, Xuan; Chan, Leighton

2016-07-01

The receiver operating characteristic (ROC) curve is a popular tool to evaluate and compare the accuracy of diagnostic tests to distinguish the diseased group from the nondiseased group when test results from tests are continuous or ordinal. A complicated data setting occurs when multiple tests are measured on abnormal and normal locations from the same subject and the measurements are clustered within the subject. Although least squares regression methods can be used for the estimation of ROC curve from correlated data, how to develop the least squares methods to estimate the ROC curve from the clustered data has not been studied. Also, the statistical properties of the least squares methods under the clustering setting are unknown. In this article, we develop the least squares ROC methods to allow the baseline and link functions to differ, and more importantly, to accommodate clustered data with discrete covariates. The methods can generate smooth ROC curves that satisfy the inherent continuous property of the true underlying curve. The least squares methods are shown to be more efficient than the existing nonparametric ROC methods under appropriate model assumptions in simulation studies. We apply the methods to a real example in the detection of glaucomatous deterioration. We also derive the asymptotic properties of the proposed methods. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Least Squares Solution of Small Sample Multiple-Master PSInSAR System

NASA Astrophysics Data System (ADS)

Zhang, Lei; Ding, Xiao Li; Lu, Zhong

2010-03-01

In this paper we propose a least squares based approach for multi-temporal SAR interferometry that allows to estimate the deformation rate with no need of phase unwrapping. The approach utilizes a series of multi-master wrapped differential interferograms with short baselines and only focuses on the arcs constructed by two nearby points at which there are no phase ambiguities. During the estimation an outlier detector is used to identify and remove the arcs with phase ambiguities, and pseudoinverse of priori variance component matrix is taken as the weight of correlated observations in the model. The parameters at points can be obtained by an indirect adjustment model with constraints when several reference points are available. The proposed approach is verified by a set of simulated data.

Application of Fourier transform near-infrared spectroscopy combined with high-performance liquid chromatography in rapid and simultaneous determination of essential components in crude Radix Scrophulariae.

PubMed

Li, Xiaomeng; Fang, Dansi; Cong, Xiaodong; Cao, Gang; Cai, Hao; Cai, Baochang

2012-12-01

A method is described using rapid and sensitive Fourier transform near-infrared spectroscopy combined with high-performance liquid chromatography-diode array detection for the simultaneous identification and determination of four bioactive compounds in crude Radix Scrophulariae samples. Partial least squares regression is selected as the analysis type and multiplicative scatter correction, second derivative, and Savitzky-Golay filter were adopted for the spectral pretreatment. The correlation coefficients (R) of the calibration models were above 0.96 and the root mean square error of predictions were under 0.028. The developed models were applied to unknown samples with satisfactory results. The established method was validated and can be applied to the intrinsic quality control of crude Radix Scrophulariae.

Covariance Matrix Estimation for Massive MIMO

NASA Astrophysics Data System (ADS)

Upadhya, Karthik; Vorobyov, Sergiy A.

2018-04-01

We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

Correcting Four Similar Correlational Measures for Attenuation Due to Errors of Measurement in the Dependent Variable: Eta, Epsilon, Omega, and Intraclass r.

ERIC Educational Resources Information Center

Stanley, Julian C.; Livingston, Samuel A.

Besides the ubiquitous Pearson product-moment r, there are a number of other measures of relationship that are attenuated by errors of measurement and for which the relationship between true measures can be estimated. Among these are the correlation ratio (eta squared), Kelley's unbiased correlation ratio (epsilon squared), Hays' omega squared,…

Performance Analysis of a De-correlated Modified Code Tracking Loop for Synchronous DS-CDMA System under Multiuser Environment

NASA Astrophysics Data System (ADS)

Wu, Ya-Ting; Wong, Wai-Ki; Leung, Shu-Hung; Zhu, Yue-Sheng

This paper presents the performance analysis of a De-correlated Modified Code Tracking Loop (D-MCTL) for synchronous direct-sequence code-division multiple-access (DS-CDMA) systems under multiuser environment. Previous studies have shown that the imbalance of multiple access interference (MAI) in the time lead and time lag portions of the signal causes tracking bias or instability problem in the traditional correlating tracking loop like delay lock loop (DLL) or modified code tracking loop (MCTL). In this paper, we exploit the de-correlating technique to combat the MAI at the on-time code position of the MCTL. Unlike applying the same technique to DLL which requires an extensive search algorithm to compensate the noise imbalance which may introduce small tracking bias under low signal-to-noise ratio (SNR), the proposed D-MCTL has much lower computational complexity and exhibits zero tracking bias for the whole range of SNR, regardless of the number of interfering users. Furthermore, performance analysis and simulations based on Gold codes show that the proposed scheme has better mean square tracking error, mean-time-to-lose-lock and near-far resistance than the other tracking schemes, including traditional DLL (T-DLL), traditional MCTL (T-MCTL) and modified de-correlated DLL (MD-DLL).

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Least-Squares Approximation of an Improper Correlation Matrix by a Proper One.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

1989-01-01

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

Fitting a function to time-dependent ensemble averaged data.

PubMed

Fogelmark, Karl; Lomholt, Michael A; Irbäck, Anders; Ambjörnsson, Tobias

2018-05-03

Time-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these averages (for instance, squared displacements) with a function and extract parameters (such as diffusion constants). A commonly overlooked challenge in such function fitting procedures is that fluctuations around mean values, by construction, exhibit temporal correlations. We show that the only available general purpose function fitting methods, correlated chi-square method and the weighted least squares method (which neglects correlation), fail at either robust parameter estimation or accurate error estimation. We remedy this by deriving a new closed-form error estimation formula for weighted least square fitting. The new formula uses the full covariance matrix, i.e., rigorously includes temporal correlations, but is free of the robustness issues, inherent to the correlated chi-square method. We demonstrate its accuracy in four examples of importance in many fields: Brownian motion, damped harmonic oscillation, fractional Brownian motion and continuous time random walks. We also successfully apply our method, weighted least squares including correlation in error estimation (WLS-ICE), to particle tracking data. The WLS-ICE method is applicable to arbitrary fit functions, and we provide a publically available WLS-ICE software.

Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

2017-09-01

In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

A Reactive Balance Rating Method that Correlates with Kinematics after Trip-Like Perturbations on a Treadmill and Fall Risk Among Residents of Older Adult Congregate Housing.

PubMed

Madigan, Michael L; Aviles, Jessica; Allin, Leigh J; Nussbaum, Maury A; Alexander, Neil B

2018-04-16

A growing number of studies are using modified treadmills to train reactive balance after trip-like perturbations that require multiple steps to recover balance. The goal of this study was thus to develop and validate a low-tech reactive balance rating method in the context of trip-like treadmill perturbations to facilitate the implementation of this training outside the research setting. Thirty-five residents of five senior congregate housing facilities participated in the study. Subjects completed a series of reactive balance tests on a modified treadmill from which the reactive balance rating was determined, along with a battery of standard clinical balance and mobility tests that predict fall risk. We investigated the strength of correlation between the reactive balance rating and reactive balance kinematics. We compared the strength of correlation between the reactive balance rating and clinical tests predictive of fall risk, with the strength of correlation between reactive balance kinematics and the same clinical tests. We also compared the reactive balance rating between subjects predicted to be at a high or low risk of falling. The reactive balance rating was correlated with reactive balance kinematics (Spearman's rho squared = .04 - .30), exhibited stronger correlations with clinical tests than most kinematic measures (Spearman's rho squared = .00 - .23), and was 42-60% lower among subjects predicted to be at a high risk for falling. The reactive balance rating method may provide a low-tech, valid measure of reactive balance kinematics, and an indicator of fall risk, after trip-like postural perturbations.

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

The channel radius and energy of cloud-to-ground lightning discharge plasma with multiple return strokes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xuejuan; Yuan, Ping; Cen, Jianyong

2014-03-15

Using the spectra of a cloud-to-ground (CG) lightning flash with multiple return strokes and combining with the synchronous radiated electrical field information, the linear charge density, the channel radius, the energy per unit length, the thermal energy, and the energy of dissociation and ionization in discharge channel are calculated with the aid of an electrodynamic model of lightning. The conclusion that the initial radius of discharge channel is determined by the duration of the discharge current is confirmed. Moreover, the correlativity of several parameters has been analyzed first. The results indicate that the total intensity of spectra is positive correlatedmore » to the channel initial radius. The ionization and thermal energies have a linear relationship, and the dissociation energy is correlated positively to the ionization and thermal energies, the energy per unit length is in direct proportion to the square of initial radius in different strokes of one CG lightning.« less

Factors associated with endodontic flare-ups: a prospective study.

PubMed

Imura, N; Zuolo, M L

1995-09-01

The purpose of this prospective study was to assess the incidence of flare-ups (a severe problem requiring an unscheduled visit and treatment) among patients who received endodontic treatment by the two authors in their respective practices during a period of one year, and also to examine the correlation with pre-operative and operative variables. The results showed an incidence of 1.58% for flare-ups from 1012 endodontically treated teeth. Statistical analysis using the chi-square test (P<0.05) indicated that flare-ups were found to be positively correlated with multiple appointments, retreatment cases, periradicular pain prior to treatment, presence of radiolucent lesions, and patients taking analgesic or anti-inflammatory drugs. In contrast, there was no correlation between flare-up, and age, sex, different arch/tooth groups and the status of the pulp.

Correlated Noise: How it Breaks NMF, and What to Do About It.

PubMed

Plis, Sergey M; Potluru, Vamsi K; Lane, Terran; Calhoun, Vince D

2011-01-12

Non-negative matrix factorization (NMF) is a problem of decomposing multivariate data into a set of features and their corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it, even when given freedom to be able to represent the noise as a separate feature. To cope with this issue, we present an algorithm for NMF with a generalized least squares objective function (glsNMF) and derive multiplicative updates for the method together with proving their convergence. The new algorithm successfully recovers the true representation from the noisy data. Robust performance can make glsNMF a valuable tool for analyzing empirical data.

Correlated Noise: How it Breaks NMF, and What to Do About It

PubMed Central

Plis, Sergey M.; Potluru, Vamsi K.; Lane, Terran; Calhoun, Vince D.

2010-01-01

Non-negative matrix factorization (NMF) is a problem of decomposing multivariate data into a set of features and their corresponding activations. When applied to experimental data, NMF has to cope with noise, which is often highly correlated. We show that correlated noise can break the Donoho and Stodden separability conditions of a dataset and a regular NMF algorithm will fail to decompose it, even when given freedom to be able to represent the noise as a separate feature. To cope with this issue, we present an algorithm for NMF with a generalized least squares objective function (glsNMF) and derive multiplicative updates for the method together with proving their convergence. The new algorithm successfully recovers the true representation from the noisy data. Robust performance can make glsNMF a valuable tool for analyzing empirical data. PMID:23750288

Search for gravitational waves from LIGO-Virgo science run and data interpretation

NASA Astrophysics Data System (ADS)

Biswas, Rahul

Search for gravitational wave events was performed on data jointly taken during LIGO's fifth science run (S5) and Virgo's first science mn (VSR1). The data taken during this period was broken down into five separate months. I shall report the analysis performed on one of these months. Apart from the search, I shall describe the work related to estimation of rate based on the loudest event in the search. I shall demonstrate methods used in construction of rate intervals at 90% confidence level and combination of rates from multiple experiments of similar duration. To have confidence in our detection, accurate estimation of false alarm probability (F.A.P.) associated with the event candidate is required. Current false alarm estimation techniques limit our ability to measure the F.A.P. to about 1 in 100. I shall describe a method that significantly improves this estimate using information from multiple detectors. Besides accurate knowledge of F.A.P., detection is also dependent on our ability to distinguish real signals to those from noise. Several tests exist which use the quality of the signal to differentiate between real and noise signal. The chi-square test is one such computationally expensive test applied in our search; we shall understand the dependence of the chi-square parameter on the signal to noise ratio (SNR) for a given signal, which will help us to model the chi-square parameter based on SNR. The two detectors at Hanford, WA, H1(4km) and H2(2km), share the same vacuum system and hence their noise is correlated. Our present method of background estimation cannot capture this correlation and often underestimates the background when only H1 and H2 are operating. I shall describe a novel method of time reversed filtering to correctly estimate the background.

A new multidimensional measure of African adolescents' perceptions of teachers' behaviors.

PubMed

Mboya, M M

1994-04-01

The Perceived Teacher Behavior Inventory was designed to measure three dimensions of students' perceptions of the behaviors of their teachers. This research was conducted to assess the statistical validity and reliability of the instrument administered to 770 students attending two coeducational high schools in Cape Town, South Africa. Factor analysis clearly identified three subscales indicating that the instrument distinguished the students' perceptions of their teachers' behaviors in three areas. Estimates of internal consistency of the subscales were assessed using the squared multiple correlation as the index of reliability.

Performance Analysis of Blind Subspace-Based Signature Estimation Algorithms for DS-CDMA Systems with Unknown Correlated Noise

NASA Astrophysics Data System (ADS)

Zarifi, Keyvan; Gershman, Alex B.

2006-12-01

We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.

A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.

PubMed

Cao, Cheng; Akalin Acar, Zeynep; Kreutz-Delgado, Kenneth; Makeig, Scott

2012-01-01

Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.

Speckle evolution with multiple steps of least-squares phase removal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen Mingzhou; Dainty, Chris; Roux, Filippus S.

2011-08-15

We study numerically the evolution of speckle fields due to the annihilation of optical vortices after the least-squares phase has been removed. A process with multiple steps of least-squares phase removal is carried out to minimize both vortex density and scintillation index. Statistical results show that almost all the optical vortices can be removed from a speckle field, which finally decays into a quasiplane wave after such an iterative process.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Detection of Glutamic Acid in Oilseed Rape Leaves Using Near Infrared Spectroscopy and the Least Squares-Support Vector Machine

PubMed Central

Bao, Yidan; Kong, Wenwen; Liu, Fei; Qiu, Zhengjun; He, Yong

2012-01-01

Amino acids are quite important indices to indicate the growth status of oilseed rape under herbicide stress. Near infrared (NIR) spectroscopy combined with chemometrics was applied for fast determination of glutamic acid in oilseed rape leaves. The optimal spectral preprocessing method was obtained after comparing Savitzky-Golay smoothing, standard normal variate, multiplicative scatter correction, first and second derivatives, detrending and direct orthogonal signal correction. Linear and nonlinear calibration methods were developed, including partial least squares (PLS) and least squares-support vector machine (LS-SVM). The most effective wavelengths (EWs) were determined by the successive projections algorithm (SPA), and these wavelengths were used as the inputs of PLS and LS-SVM model. The best prediction results were achieved by SPA-LS-SVM (Raw) model with correlation coefficient r = 0.9943 and root mean squares error of prediction (RMSEP) = 0.0569 for prediction set. These results indicated that NIR spectroscopy combined with SPA-LS-SVM was feasible for the fast and effective detection of glutamic acid in oilseed rape leaves. The selected EWs could be used to develop spectral sensors, and the important and basic amino acid data were helpful to study the function mechanism of herbicide. PMID:23203052

Assessment of blood donation intention among medical students in Pakistan--An application of theory of planned behavior.

PubMed

Faqah, Anadil; Moiz, Bushra; Shahid, Fatima; Ibrahim, Mariam; Raheem, Ahmed

2015-12-01

Theory of Planned Behavior proposes a model which can measure how human actions are guided. It has been successfully utilized in the context of blood donation. We employed a decision-making framework to determine the intention of blood donation among medical students who have never donated blood before the study. Survey responses were collected from 391 medical students from four various universities on a defined questionnaire. The tool composed of 20 questions that were formulated to explain donation intention based on theory of planned behavior. The construct included questions related to attitude, subjective norm and perceived behavior control, descriptive norm, moral norm, anticipated regret, donation anxiety and religious norm. Pearson's correlational relationships were measured between independent and dependent variables of intention to donate blood. ANOVA was applied to observe the model fit; a value of 0.000 was considered statistically significant. A multiple regression analysis was conducted to explore the relative importance of the main independent variables in the prediction of intention. Multi-collinearity was also evaluated to determine that various independent variables determine the intention. The reliability of measures composed of two items was assessed using inter-item correlations. Three hundred and ninety-one medical students (M:F; 1:2.2) with mean age of 21.96 years ± 1.95 participated in this study. Mean item score was 3.8 ± 0.83. Multiple regression analysis suggested that perceived behavioral control, anticipated regret and attitude were the most influential factors in determining intention of blood donation. Donation anxiety was least correlated and in fact bore a negative correlation with intention. ANOVA computed an F value of 199.082 with a p-value of 0.000 indicating fitness of model. The value of R square and adjusted R square was 0.811 and 0.807 respectively indicating strong correlation between various independent and dependent variables. Medical students as novice blood donors showed a positive attitude toward blood donation. Theory of planned behavior can be successfully utilized in determining the antecedents toward blood donation behavior. Copyright © 2015 Elsevier Ltd. All rights reserved.

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

A comparison of two indices for the intraclass correlation coefficient.

PubMed

Shieh, Gwowen

2012-12-01

In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.

Soil fungal diversity in natural grasslands of the Tibetan Plateau: associations with plant diversity and productivity.

PubMed

Yang, Teng; Adams, Jonathan M; Shi, Yu; He, Jin-Sheng; Jing, Xin; Chen, Litong; Tedersoo, Leho; Chu, Haiyan

2017-07-01

Previous studies have revealed inconsistent correlations between fungal diversity and plant diversity from local to global scales, and there is a lack of information about the diversity-diversity and productivity-diversity relationships for fungi in alpine regions. Here we investigated the internal relationships between soil fungal diversity, plant diversity and productivity across 60 grassland sites on the Tibetan Plateau, using Illumina sequencing of the internal transcribed spacer 2 (ITS2) region for fungal identification. Fungal alpha and beta diversities were best explained by plant alpha and beta diversities, respectively, when accounting for environmental drivers and geographic distance. The best ordinary least squares (OLS) multiple regression models, partial least squares regression (PLSR) and variation partitioning analysis (VPA) indicated that plant richness was positively correlated with fungal richness. However, no correlation between plant richness and fungal richness was evident for fungal functional guilds when analyzed individually. Plant productivity showed a weaker relationship to fungal diversity which was intercorrelated with other factors such as plant diversity, and was thus excluded as a main driver. Our study points to a predominant effect of plant diversity, along with other factors such as carbon : nitrogen (C : N) ratio, soil phosphorus and dissolved organic carbon, on soil fungal richness. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Linear Least Squares for Correlated Data

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1988-01-01

Throughout the literature authors have consistently discussed the suspicion that regression results were less than satisfactory when the independent variables were correlated. Camm, Gulledge, and Womer, and Womer and Marcotte provide excellent applied examples of these concerns. Many authors have obtained partial solutions for this problem as discussed by Womer and Marcotte and Wonnacott and Wonnacott, which result in generalized least squares algorithms to solve restrictive cases. This paper presents a simple but relatively general multivariate method for obtaining linear least squares coefficients which are free of the statistical distortion created by correlated independent variables.

Use of ultrasonic array method for positioning multiple partial discharge sources in transformer oil.

PubMed

Xie, Qing; Tao, Junhan; Wang, Yongqiang; Geng, Jianghai; Cheng, Shuyi; Lü, Fangcheng

2014-08-01

Fast and accurate positioning of partial discharge (PD) sources in transformer oil is very important for the safe, stable operation of power systems because it allows timely elimination of insulation faults. There is usually more than one PD source once an insulation fault occurs in the transformer oil. This study, which has both theoretical and practical significance, proposes a method of identifying multiple PD sources in the transformer oil. The method combines the two-sided correlation transformation algorithm in the broadband signal focusing and the modified Gerschgorin disk estimator. The method of classification of multiple signals is used to determine the directions of arrival of signals from multiple PD sources. The ultrasonic array positioning method is based on the multi-platform direction finding and the global optimization searching. Both the 4 × 4 square planar ultrasonic sensor array and the ultrasonic array detection platform are built to test the method of identifying and positioning multiple PD sources. The obtained results verify the validity and the engineering practicability of this method.

On squares of representations of compact Lie algebras

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeier, Robert, E-mail: robert.zeier@ch.tum.de; Zimborás, Zoltán, E-mail: zimboras@gmail.com

We study how tensor products of representations decompose when restricted from a compact Lie algebra to one of its subalgebras. In particular, we are interested in tensor squares which are tensor products of a representation with itself. We show in a classification-free manner that the sum of multiplicities and the sum of squares of multiplicities in the corresponding decomposition of a tensor square into irreducible representations has to strictly grow when restricted from a compact semisimple Lie algebra to a proper subalgebra. For this purpose, relevant details on tensor products of representations are compiled from the literature. Since the summore » of squares of multiplicities is equal to the dimension of the commutant of the tensor-square representation, it can be determined by linear-algebra computations in a scenario where an a priori unknown Lie algebra is given by a set of generators which might not be a linear basis. Hence, our results offer a test to decide if a subalgebra of a compact semisimple Lie algebra is a proper one without calculating the relevant Lie closures, which can be naturally applied in the field of controlled quantum systems.« less

Use of electronic cigarettes and alternative tobacco products among Romanian adolescents.

PubMed

Nădăşan, Valentin; Foley, Kristie L; Pénzes, Melinda; Paulik, Edit; Mihăicuţă, Ştefan; Ábrám, Zoltán; Bálint, Jozsef; Urbán, Robert

2016-03-01

To assess socio-demographic and smoking-related correlates of e-cigarette and alternative tobacco products (ATPs) use in a multi-ethnic group of adolescents in Tîrgu Mures, Romania. The cross-sectional study included 1835 high school students from Tirgu Mures, Romania. Socio-demographic variables and data about smoking and e-cigarettes and ATP use were collected using an online questionnaire. Chi-square tests or one-way ANOVA were applied to compare never smokers, non-current smokers, and current smokers. Multiple logistic regression was conducted to determine the correlates of e-cigarettes and ATP use. The most frequently tried non-cigarette nicotine and tobacco products were e-cigarette (38.5 %), cigar (31.4 %) and waterpipe (21.1 %). Ever trying and current use of cigarettes were the most important correlates of e-cigarette and ATPs use. Sex, ethnicity, sensation seeking and perceived peer smoking were correlates of several ATPs use. The results of this study may inform the development of tailored tobacco control programs.

A note on implementation of decaying product correlation structures for quasi-least squares.

PubMed

Shults, Justine; Guerra, Matthew W

2014-08-30

This note implements an unstructured decaying product matrix via the quasi-least squares approach for estimation of the correlation parameters in the framework of generalized estimating equations. The structure we consider is fairly general without requiring the large number of parameters that are involved in a fully unstructured matrix. It is straightforward to show that the quasi-least squares estimators of the correlation parameters yield feasible values for the unstructured decaying product structure. Furthermore, subject to conditions that are easily checked, the quasi-least squares estimators are valid for longitudinal Bernoulli data. We demonstrate implementation of the structure in a longitudinal clinical trial with both a continuous and binary outcome variable. Copyright © 2014 John Wiley & Sons, Ltd.

Statistical analysis of trypanosomes' motility

NASA Astrophysics Data System (ADS)

Zaburdaev, Vasily; Uppaluri, Sravanti; Pfohl, Thomas; Engstler, Markus; Stark, Holger; Friedrich, Rudolf

2010-03-01

Trypanosome is a parasite causing the sleeping sickness. The way it moves in the blood stream and penetrates various obstacles is the area of active research. Our goal was to investigate a free trypanosomes' motion in the planar geometry. Our analysis of trypanosomes' trajectories reveals that there are two correlation times - one is associated with a fast motion of its body and the second one with a slower rotational diffusion of the trypanosome as a point object. We propose a system of Langevin equations to model such motion. One of its peculiarities is the presence of multiplicative noise predicting higher level of noise for higher velocity of the trypanosome. Theoretical and numerical results give a comprehensive description of the experimental data such as the mean squared displacement, velocity distribution and auto-correlation function.

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods

NASA Astrophysics Data System (ADS)

Müller, Aline Lima Hermes; Picoloto, Rochele Sogari; Mello, Paola de Azevedo; Ferrão, Marco Flores; dos Santos, Maria de Fátima Pereira; Guimarães, Regina Célia Lourenço; Müller, Edson Irineu; Flores, Erico Marlon Moraes

2012-04-01

Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm-1). This model produced a RMSECV of 400 mg kg-1 S and RMSEP of 420 mg kg-1 S, showing a correlation coefficient of 0.990.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

On the equivalence of the RTI and SVM approaches to time correlated analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croft, S.; Favalli, A.; Henzlova, D.

2014-11-21

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could alsomore » use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.« less

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

A predictive assessment of genetic correlations between traits in chickens using markers.

PubMed

Momen, Mehdi; Mehrgardi, Ahmad Ayatollahi; Sheikhy, Ayoub; Esmailizadeh, Ali; Fozi, Masood Asadi; Kranis, Andreas; Valente, Bruno D; Rosa, Guilherme J M; Gianola, Daniel

2017-02-01

Genomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations. A multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λ G + (1 - λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the "optimum" λ was determined using cross-validation. Estimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW-HHP and BM-HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together. Our findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection.

Radiographic assessment of third molars development and it's relation to dental and chronological age in an Iranian population.

PubMed

Monirifard, Mohamad; Yaraghi, Navid; Vali, Ava; Vali, Asana; Vali, Amrita

2015-01-01

The aim of the present study was to estimate chronological age based on third molar development and to determine the association between dental age and third molar calcification stages. In this cross-sectional study, 505 digital panoramic radiographs of 223 males (44.2%) and 282 females (55.8%) between the age of 6 and 17 were selected from patients who were treated in Departments of Pediatrics and Orthodontics of Isfahan University of Medical Sciences between the years of 2009 and 2013. Correlation between chronological age and third molar development was analyzed with SPSS 21 using Spearman's Rank correlation coefficient, Chi-square test and multiple regression statistical tests (P < 0.05). All third molars demonstrated a highly significant correlation with dental age (P < 0.001). The teeth showing the highest relationship with dental age were mandibular left third molar in males and mandibular right third molar in females (r s = 0.072). When multiple regression was used to predict dental age based on molar calcification stage, the only significant correlation was between maxillary left third molar in males (P < 0.05). There was no statistically significant correlation for any of third molars in females. Relationship between chronological age and molars development stage was significant in all age subgroups and in both gender (P < 0.001). Strong correlation was observed between left third molars and dental age in males. Results showed that third molar calcification stage can be used as an age predictor and in general mandibular teeth seems to be more reliable for this purpose in both genders and in all ages.

Orthogonal Chirp-Based Ultrasonic Positioning

PubMed Central

Khyam, Mohammad Omar; Ge, Shuzhi Sam; Li, Xinde; Pickering, Mark

2017-01-01

This paper presents a chirp based ultrasonic positioning system (UPS) using orthogonal chirp waveforms. In the proposed method, multiple transmitters can simultaneously transmit chirp signals, as a result, it can efficiently utilize the entire available frequency spectrum. The fundamental idea behind the proposed multiple access scheme is to utilize the oversampling methodology of orthogonal frequency-division multiplexing (OFDM) modulation and orthogonality of the discrete frequency components of a chirp waveform. In addition, the proposed orthogonal chirp waveforms also have all the advantages of a classical chirp waveform. Firstly, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic (US) positioning. For an operational range of approximately 1000 mm, the positioning root-mean-square-errors (RMSEs) &90% error were 4.54 mm and 6.68 mm respectively. PMID:28448454

Orthogonal Chirp-Based Ultrasonic Positioning.

PubMed

Khyam, Mohammad Omar; Ge, Shuzhi Sam; Li, Xinde; Pickering, Mark

2017-04-27

This paper presents a chirp based ultrasonic positioning system (UPS) using orthogonal chirp waveforms. In the proposed method, multiple transmitters can simultaneously transmit chirp signals, as a result, it can efficiently utilize the entire available frequency spectrum. The fundamental idea behind the proposed multiple access scheme is to utilize the oversampling methodology of orthogonal frequency-division multiplexing (OFDM) modulation and orthogonality of the discrete frequency components of a chirp waveform. In addition, the proposed orthogonal chirp waveforms also have all the advantages of a classical chirp waveform. Firstly, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic (US) positioning. For an operational range of approximately 1000 mm, the positioning root-mean-square-errors (RMSEs) &90% error were 4.54 mm and 6.68 mm respectively.

Synchronization of tunable asymmetric square-wave pulses in delay-coupled optoelectronic oscillators.

PubMed

Martínez-Llinàs, Jade; Colet, Pere; Erneux, Thomas

2015-03-01

We consider a model for two delay-coupled optoelectronic oscillators under positive delayed feedback as prototypical to study the conditions for synchronization of asymmetric square-wave oscillations, for which the duty cycle is not half of the period. We show that the scenario arising for positive feedback is much richer than with negative feedback. First, it allows for the coexistence of multiple in- and out-of-phase asymmetric periodic square waves for the same parameter values. Second, it is tunable: The period of all the square-wave periodic pulses can be tuned with the ratio of the delays, and the duty cycle of the asymmetric square waves can be changed with the offset phase while the total period remains constant. Finally, in addition to the multiple in- and out-of-phase periodic square waves, low-frequency periodic asymmetric solutions oscillating in phase may coexist for the same values of the parameters. Our analytical results are in agreement with numerical simulations and bifurcation diagrams obtained by using continuation techniques.

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

The Shame and Guilt Scales of the Test of Self-Conscious Affect-Adolescent (TOSCA-A): Factor Structure, Concurrent and Discriminant Validity, and Measurement and Structural Invariance Across Ratings of Males and Females.

PubMed

Watson, Shaun; Gomez, Rapson; Gullone, Eleonora

2017-06-01

This study examined various psychometric properties of the items comprising the shame and guilt scales of the Test of Self-Conscious Affect-Adolescent. A total of 563 adolescents (321 females and 242 males) completed these scales, and also measures of depression and empathy. Confirmatory factor analysis provided support for an oblique two-factor model, with the originally proposed shame and guilt items comprising shame and guilt factors, respectively. Also, shame correlated with depression positively and had no relation with empathy. Guilt correlated with depression negatively and with empathy positively. Thus, there was support for the convergent and discriminant validity of the shame and guilt factors. Multiple-group confirmatory factor analysis comparing females and males, based on the chi-square difference test, supported full metric invariance, the intercept invariance of 26 of the 30 shame and guilt items, and higher latent mean scores among females for both shame and guilt. Comparisons based on the difference in root mean squared error of approximation values supported full measurement invariance and no gender difference for latent mean scores. The psychometric and practical implications of the findings are discussed.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering

PubMed Central

Almeida, Fernando R.; Brayner, Angelo; Rodrigues, Joel J. P. C.; Maia, Jose E. Bessa

2017-01-01

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering. To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE). PMID:28590450

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

Improving Multidimensional Wireless Sensor Network Lifetime Using Pearson Correlation and Fractal Clustering.

PubMed

Almeida, Fernando R; Brayner, Angelo; Rodrigues, Joel J P C; Maia, Jose E Bessa

2017-06-07

An efficient strategy for reducing message transmission in a wireless sensor network (WSN) is to group sensors by means of an abstraction denoted cluster. The key idea behind the cluster formation process is to identify a set of sensors whose sensed values present some data correlation. Nowadays, sensors are able to simultaneously sense multiple different physical phenomena, yielding in this way multidimensional data. This paper presents three methods for clustering sensors in WSNs whose sensors collect multidimensional data. The proposed approaches implement the concept of multidimensional behavioral clustering . To show the benefits introduced by the proposed methods, a prototype has been implemented and experiments have been carried out on real data. The results prove that the proposed methods decrease the amount of data flowing in the network and present low root-mean-square error (RMSE).

Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2012-01-01

A technique is presented for initializing multiple discrete finite element model (FEM) mode sets for certain types of flight dynamics formulations that rely on superposition of orthogonal modes for modeling the elastic response. Such approaches are commonly used for modeling launch vehicle dynamics, and challenges arise due to the rapidly time-varying nature of the rigid-body and elastic characteristics. By way of an energy argument, a quadratic inequality constrained least squares (LSQI) algorithm is employed to e ect a smooth transition from one set of FEM eigenvectors to another with no requirement that the models be of similar dimension or that the eigenvectors be correlated in any particular way. The physically unrealistic and controversial method of eigenvector interpolation is completely avoided, and the discrete solution approximates that of the continuously varying system. The real-time computational burden is shown to be negligible due to convenient features of the solution method. Simulation results are presented, and applications to staging and other discontinuous mass changes are discussed

Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

2010-01-01

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

Comparison of face types in Chinese women using three-dimensional computed tomography.

PubMed

Zhou, Rong-Rong; Zhao, Qi-Ming; Liu, Miao

2015-04-01

This study compared inverted triangle and square faces of 21 young Chinese Han women (18-25 years old) using three-dimensional computed tomography images retrieved from a records database. In this study, 11 patients had inverted triangle faces and 10 had square faces. The anatomic features were examined and compared. There were significant differences in lower face width, lower face height, masseter thickness, middle/lower face width ratio, and lower face width/height ratio between the two facial types (p < 0.01). Lower face width was positively correlated with masseter thickness and negatively correlated with gonial angle. Lower face height was positively correlated with gonial angle and negatively correlated with masseter thickness, and gonial angle was negatively correlated with masseter thickness. In young Chinese Han women, inverted triangle faces and square faces differ significantly in masseter thickness and lower face height. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Least-Squares Approximation of an Improper by a Proper Correlation Matrix Using a Semi-Infinite Convex Program. Research Report 87-7.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based on a solution for C. I. Mosier's oblique Procrustes rotation problem offered by J. M. F. ten Berge and K. Nevels (1977). It is shown that the minimization problem…

Near-infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Parching Process of Traditional Chinese Medicine Based on Two Kinds of Chemical Indicators.

PubMed

Li, Kaiyue; Wang, Weiying; Liu, Yanping; Jiang, Su; Huang, Guo; Ye, Liming

2017-01-01

The active ingredients and thus pharmacological efficacy of traditional Chinese medicine (TCM) at different degrees of parching process vary greatly. Near-infrared spectroscopy (NIR) was used to develop a new method for rapid online analysis of TCM parching process, using two kinds of chemical indicators (5-(hydroxymethyl) furfural [5-HMF] content and 420 nm absorbance) as reference values which were obviously observed and changed in most TCM parching process. Three representative TCMs, Areca ( Areca catechu L.), Malt ( Hordeum Vulgare L.), and Hawthorn ( Crataegus pinnatifida Bge.), were used in this study. With partial least squares regression, calibration models of NIR were generated based on two kinds of reference values, i.e. 5-HMF contents measured by high-performance liquid chromatography (HPLC) and 420 nm absorbance measured by ultraviolet-visible spectroscopy (UV/Vis), respectively. In the optimized models for 5-HMF, the root mean square errors of prediction (RMSEP) for Areca, Malt, and Hawthorn was 0.0192, 0.0301, and 0.2600 and correlation coefficients ( R cal ) were 99.86%, 99.88%, and 99.88%, respectively. Moreover, in the optimized models using 420 nm absorbance as reference values, the RMSEP for Areca, Malt, and Hawthorn was 0.0229, 0.0096, and 0.0409 and R cal were 99.69%, 99.81%, and 99.62%, respectively. NIR models with 5-HMF content and 420 nm absorbance as reference values can rapidly and effectively identify three kinds of TCM in different parching processes. This method has great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online analysis and quality control in TCM industrial manufacturing process. Near-infrared spectroscopy.(NIR) was used to develop a new method for online analysis of traditional Chinese medicine.(TCM) parching processCalibration and validation models of Areca, Malt, and Hawthorn were generated by partial least squares regression using 5.(hydroxymethyl) furfural contents and 420.nm absorbance as reference values, respectively, which were main indicator components during parching process of most TCMThe established NIR models of three TCMs had low root mean square errors of prediction and high correlation coefficientsThe NIR method has great promise for use in TCM industrial manufacturing processes for rapid online analysis and quality control. Abbreviations used: NIR: Near-infrared Spectroscopy; TCM: Traditional Chinese medicine; Areca: Areca catechu L.; Hawthorn: Crataegus pinnatifida Bge.; Malt: Hordeum vulgare L.; 5-HMF: 5-(hydroxymethyl) furfural; PLS: Partial least squares; D: Dimension faction; SLS: Straight line subtraction, MSC: Multiplicative scatter correction; VN: Vector normalization; RMSECV: Root mean square errors of cross-validation; RMSEP: Root mean square errors of validation; R cal : Correlation coefficients; RPD: Residual predictive deviation; PAT: Process analytical technology; FDA: Food and Drug Administration; ICH: International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use.

Influence of a perturbation in the Gyrator domain for a joint transform correlator-based encryption system

NASA Astrophysics Data System (ADS)

Vilardy, Juan M.; Millán, María. S.; Pérez-Cabré, Elisabet

2017-08-01

We present the results of the noise and occlusion tests in the Gyrator domain (GD) for a joint transform correlator-based encryption system. This encryption system was recently proposed and it was implemented by using a fully phase nonzero-order joint transform correlator (JTC) and the Gyrator transform (GT). The decryption system was based on two successive GTs. In this paper, we make several numerical simulations in order to test the performance and robustness of the JTC-based encryption-decryption system in the GD when the encrypted image is corrupted by noise or occlusion. The encrypted image is affected by additive and multiplicative noise. We also test the effect of data loss due to partial occlusion of the encrypted information. Finally, we evaluate the performance and robustness of the encryption-decryption system in the GD by using the metric of the root mean square error (RMSE) between the original image and the decrypted image when the encrypted image is degraded by noise or modified by occlusion.

Using multiple calibration sets to improve the quantitative accuracy of partial least squares (PLS) regression on open-path fourier transform infrared (OP/FT-IR) spectra of ammonia over wide concentration ranges

USDA-ARS?s Scientific Manuscript database

A technique of using multiple calibration sets in partial least squares regression (PLS) was proposed to improve the quantitative determination of ammonia from open-path Fourier transform infrared spectra. The spectra were measured near animal farms, and the path-integrated concentration of ammonia...

Maritime Adaptive Optics Beam Control

DTIC Science & Technology

2010-09-01

Liquid Crystal LMS Least Mean Square MIMO Multiple- Input Multiple-Output MMDM Micromachined Membrane Deformable Mirror MSE Mean Square Error...determine how the beam is distorted, a control computer to calculate the correction to be applied, and a corrective element, usually a deformable mirror ...during this research, an overview of the system modification is provided here. Using additional mirrors and reflecting the beam to and from an

Linearized inversion of multiple scattering seismic energy

NASA Astrophysics Data System (ADS)

Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad

2014-05-01

Internal multiples deteriorate the quality of the migrated image obtained conventionally by imaging single scattering energy. So, imaging seismic data with the single-scattering assumption does not locate multiple bounces events in their actual subsurface positions. However, imaging internal multiples properly has the potential to enhance the migrated image because they illuminate zones in the subsurface that are poorly illuminated by single scattering energy such as nearly vertical faults. Standard migration of these multiples provides subsurface reflectivity distributions with low spatial resolution and migration artifacts due to the limited recording aperture, coarse sources and receivers sampling, and the band-limited nature of the source wavelet. The resultant image obtained by the adjoint operator is a smoothed depiction of the true subsurface reflectivity model and is heavily masked by migration artifacts and the source wavelet fingerprint that needs to be properly deconvolved. Hence, we proposed a linearized least-square inversion scheme to mitigate the effect of the migration artifacts, enhance the spatial resolution, and provide more accurate amplitude information when imaging internal multiples. The proposed algorithm uses the least-square image based on single-scattering assumption as a constraint to invert for the part of the image that is illuminated by internal scattering energy. Then, we posed the problem of imaging double-scattering energy as a least-square minimization problem that requires solving the normal equation of the following form: GTGv = GTd, (1) where G is a linearized forward modeling operator that predicts double-scattered seismic data. Also, GT is a linearized adjoint operator that image double-scattered seismic data. Gradient-based optimization algorithms solve this linear system. Hence, we used a quasi-Newton optimization technique to find the least-square minimizer. In this approach, an estimate of the Hessian matrix that contains curvature information is modified at every iteration by a low-rank update based on gradient changes at every step. At each iteration, the data residual is imaged using GT to determine the model update. Application of the linearized inversion to synthetic data to image a vertical fault plane demonstrate the effectiveness of this methodology to properly delineate the vertical fault plane and give better amplitude information than the standard migrated image using the adjoint operator that takes into account internal multiples. Thus, least-square imaging of multiple scattering enhances the spatial resolution of the events illuminated by internal scattering energy. It also deconvolves the source signature and helps remove the fingerprint of the acquisition geometry. The final image is obtained by the superposition of the least-square solution based on single scattering assumption and the least-square solution based on double scattering assumption.

Summarizing slant perception with words and hands; an empirical alternative to correlations in Shaffer, McManama, Swank, Williams & Durgin (2014).

PubMed

Eves, Frank F

2015-02-01

The paper by Shaffer, McManama, Swank, Williams & Durgin (2014) uses correlations between palm-board and verbal estimates of geographical slant to argue against dissociation of the two measures. This paper reports the correlations between the verbal, visual and palm-board measures of geographical slant used by Proffitt and co-workers as a counterpoint to the analyses presented by Shaffer and colleagues. The data are for slant perception of staircases in a station (N=269), a shopping mall (N=229) and a civic square (N=109). In all three studies, modest correlations between the palm-board matches and the verbal reports were obtained. Multiple-regression analyses of potential contributors to verbal reports, however, indicated no unique association between verbal and palm-board measures. Data from three further studies (combined N=528) also show no evidence of any relationship. Shared method variance between visual and palm-board matches could account for the modest association between palm-boards and verbal reports. Copyright © 2015. Published by Elsevier B.V.

Spirituality and Resilience Among Mexican American IPV Survivors.

PubMed

de la Rosa, Iván A; Barnett-Queen, Timothy; Messick, Madeline; Gurrola, Maria

2016-12-01

Women with abusive partners use a variety of coping strategies. This study examined the correlation between spirituality, resilience, and intimate partner violence using a cross-sectional survey of 54 Mexican American women living along the U.S.-Mexico border. The meaning-making coping model provides the conceptual framework to explore how spirituality is used as a copying strategy. Multiple ordinary least squares (OLS) regression results indicate women who score higher on spirituality also report greater resilient characteristics. Poisson regression analyses revealed that an increase in level of spirituality is associated with lower number of types of abuse experienced. Clinical, programmatic, and research implications are discussed. © The Author(s) 2015.

[Determination of steviol in Stevia Rebaudiana leaves by near infrared spectroscopy].

PubMed

Tang, Qi-Kun; Wang, Yul; Wu, Yue-Jin; Min, Di; Chen, Da-Wei; Hu, Tong-Hua

2014-10-01

The objective of the present study is to develop a method for rapid determination of the content of stevioside (ST) and rebaudioside A (RA) in Stevia Rebaudiana leaves. One hundred and five samples of stevia from different areas containing ST of 0.27%-1.40% and RA of 0.61%-3.98% were used. The 105 groups' NIRS diagram was processed by different methods including subtracting a straight line (SLS), multiplicative scatter correction (MSC), first derivative (FD), second derivative (SD) and so on, and then all data were analyzed by partial least square (PLS). The study showed that SLS can be used to extracted spectra information thoroughly to analyze the contents of ST, the correlation coefficients of calibration (Re), the root-mean-square errors of calibration (RMSEC) and prediction (RMSEP), and the residual predictive deviation (RPD) were 0.986, 0.341, 1.00 and 2.8, respectively. The correlation coefficients of RA was 0.967, RMSEC was 1.50, RMSEP was 1.98 and RPD was 4.17. The results indicated that near infrared spectroscopy (NIRS) technique offers effective quantitative capability for ST and RA in Stevia Rebaudiana leaves. Then the model of stevia dried leaves was used to compare with the stevia powder near infrared model whose correlation coefficients of ST was 0.986, RMSEC was 0.32, RMSEP was 0.601 and RPD was 2.86 and the correlation coefficients of RA was 0.968, RMSEC was 1.50, RMSEP was 1.48 and RPD was 4.2. The result showed that there was no significant difference between the model of dried leaves and that of the powders. However, the dried leaves NIR model reduces the unnecessary the steps of drying and grinding in the actual detection process, saving the time and reducing the workload.

A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs.

PubMed

Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

2015-12-26

This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data.

PubMed

Gomes, Manuel; Hatfield, Laura; Normand, Sharon-Lise

2016-09-20

Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between-study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta-analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter-defibrillator devices alone to implantable cardioverter-defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Automatic Sub-Pixel Co-Registration of LandSat-8 OLI and Sentinel-2A MSI Images Using Phase Correlation and Machine Learning Based Mapping

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Roger, Jean-Claude; Vermote, Eric F.; Masek, Jeffrey G.; Justice, Christopher O.

2017-01-01

This study investigates misregistration issues between Landsat-8/OLI and Sentinel-2A/MSI at 30 m resolution, and between multi-temporal Sentinel-2A images at 10 m resolution using a phase correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30 m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10 m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear Random Forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07+/-0.02 pixels at 30 m resolution, and 0.09+/-0.05 and 0.15+/-0.06 pixels at 10 m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08+/-0.02 pixels at 30 m resolution and 0.12+/-0.06 (same Sentinel-2A orbits) and 0.20+/-0.09 (adjacent orbits) pixels at 10 m resolution.

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

A Robust Real Time Direction-of-Arrival Estimation Method for Sequential Movement Events of Vehicles.

PubMed

Liu, Huawei; Li, Baoqing; Yuan, Xiaobing; Zhou, Qianwei; Huang, Jingchang

2018-03-27

Parameters estimation of sequential movement events of vehicles is facing the challenges of noise interferences and the demands of portable implementation. In this paper, we propose a robust direction-of-arrival (DOA) estimation method for the sequential movement events of vehicles based on a small Micro-Electro-Mechanical System (MEMS) microphone array system. Inspired by the incoherent signal-subspace method (ISM), the method that is proposed in this work employs multiple sub-bands, which are selected from the wideband signals with high magnitude-squared coherence to track moving vehicles in the presence of wind noise. The field test results demonstrate that the proposed method has a better performance in emulating the DOA of a moving vehicle even in the case of severe wind interference than the narrowband multiple signal classification (MUSIC) method, the sub-band DOA estimation method, and the classical two-sided correlation transformation (TCT) method.

Total sulfur determination in residues of crude oil distillation using FT-IR/ATR and variable selection methods.

PubMed

Müller, Aline Lima Hermes; Picoloto, Rochele Sogari; de Azevedo Mello, Paola; Ferrão, Marco Flores; de Fátima Pereira dos Santos, Maria; Guimarães, Regina Célia Lourenço; Müller, Edson Irineu; Flores, Erico Marlon Moraes

2012-04-01

Total sulfur concentration was determined in atmospheric residue (AR) and vacuum residue (VR) samples obtained from petroleum distillation process by Fourier transform infrared spectroscopy with attenuated total reflectance (FT-IR/ATR) in association with chemometric methods. Calibration and prediction set consisted of 40 and 20 samples, respectively. Calibration models were developed using two variable selection models: interval partial least squares (iPLS) and synergy interval partial least squares (siPLS). Different treatments and pre-processing steps were also evaluated for the development of models. The pre-treatment based on multiplicative scatter correction (MSC) and the mean centered data were selected for models construction. The use of siPLS as variable selection method provided a model with root mean square error of prediction (RMSEP) values significantly better than those obtained by PLS model using all variables. The best model was obtained using siPLS algorithm with spectra divided in 20 intervals and combinations of 3 intervals (911-824, 823-736 and 737-650 cm(-1)). This model produced a RMSECV of 400 mg kg(-1) S and RMSEP of 420 mg kg(-1) S, showing a correlation coefficient of 0.990. Copyright © 2011 Elsevier B.V. All rights reserved.

Multiple-Coil, Pulse-Induction Metal Detector

NASA Technical Reports Server (NTRS)

Lesky, Edward S.; Reid, Alan M.; Bushong, Wilton E.; Dickey, Duane P.

1988-01-01

Multiple-head, pulse-induction metal detector scans area of 72 feet squared with combination of eight detector heads, each 3 ft. square. Head includes large primary coil inducing current in smaller secondary coils. Array of eight heads enables searcher to cover large area quickly. Pulses applied to primary coil, induced in secondary coils measured to determine whether metal present within range of detector head. Detector designed for recovery of Space Shuttle debris.

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Least Squares Procedures.

ERIC Educational Resources Information Center

Hester, Yvette

Least squares methods are sophisticated mathematical curve fitting procedures used in all classical parametric methods. The linear least squares approximation is most often associated with finding the "line of best fit" or the regression line. Since all statistical analyses are correlational and all classical parametric methods are least…

Radiographic assessment of third molars development and it's relation to dental and chronological age in an Iranian population

PubMed Central

Monirifard, Mohamad; Yaraghi, Navid; Vali, Ava; Vali, Asana; Vali, Amrita

2015-01-01

Background: The aim of the present study was to estimate chronological age based on third molar development and to determine the association between dental age and third molar calcification stages. Materials and Methods: In this cross-sectional study, 505 digital panoramic radiographs of 223 males (44.2%) and 282 females (55.8%) between the age of 6 and 17 were selected from patients who were treated in Departments of Pediatrics and Orthodontics of Isfahan University of Medical Sciences between the years of 2009 and 2013. Correlation between chronological age and third molar development was analyzed with SPSS 21 using Spearman's Rank correlation coefficient, Chi-square test and multiple regression statistical tests (P < 0.05). Results: All third molars demonstrated a highly significant correlation with dental age (P < 0.001). The teeth showing the highest relationship with dental age were mandibular left third molar in males and mandibular right third molar in females (rs = 0.072). When multiple regression was used to predict dental age based on molar calcification stage, the only significant correlation was between maxillary left third molar in males (P < 0.05). There was no statistically significant correlation for any of third molars in females. Relationship between chronological age and molars development stage was significant in all age subgroups and in both gender (P < 0.001). Conclusion: Strong correlation was observed between left third molars and dental age in males. Results showed that third molar calcification stage can be used as an age predictor and in general mandibular teeth seems to be more reliable for this purpose in both genders and in all ages. PMID:25709677

Diffusion-weighted magnetic resonance imaging in the characterization of testicular germ cell neoplasms: Effect of ROI methods on apparent diffusion coefficient values and interobserver variability.

PubMed

Tsili, Athina C; Ntorkou, Alexandra; Astrakas, Loukas; Xydis, Vasilis; Tsampalas, Stavros; Sofikitis, Nikolaos; Argyropoulou, Maria I

2017-04-01

To evaluate the difference in apparent diffusion coefficient (ADC) measurements at diffusion-weighted (DW) magnetic resonance imaging of differently shaped regions-of-interest (ROIs) in testicular germ cell neoplasms (TGCNS), the diagnostic ability of differently shaped ROIs in differentiating seminomas from nonseminomatous germ cell neoplasms (NSGCNs) and the interobserver variability. Thirty-three TGCNs were retrospectively evaluated. Patients underwent MR examinations, including DWI on a 1.5-T MR system. Two observers measured mean tumor ADCs using four distinct ROI methods: round, square, freehand and multiple small, round ROIs. The interclass correlation coefficient was analyzed to assess interobserver variability. Statistical analysis was used to compare mean ADC measurements among observers, methods and histologic types. All ROI methods showed excellent interobserver agreement, with excellent correlation (P<0.001). Multiple, small ROIs provided the lower mean ADC in TGCNs. Seminomas had lower mean ADC compared to NSGCNs for each ROI method (P<0.001). Round ROI proved the most accurate method in characterizing TGCNS. Interobserver variability in ADC measurement is excellent, irrespective of the ROI shape. Multiple, small round ROIs and round ROI proved the more accurate methods for ADC measurement in the characterization of TGCNs and in the differentiation between seminomas and NSGCNs, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

Mean-square angle-of-arrival difference between two counter-propagating spherical waves in the presence of atmospheric turbulence.

PubMed

Chen, Chunyi; Yang, Huamin; Tong, Shoufeng; Lou, Yan

2015-09-21

The mean-square angle-of-arrival (AOA) difference between two counter-propagating spherical waves in atmospheric turbulence is theoretically formulated. Closed-form expressions for the path weighting functions are obtained. It is found that the diffraction and refraction effects of turbulent cells make negative and positive contributions to the mean-square AOA difference, respectively, and the turbulent cells located at the midpoint of the propagation path have no contributions to the mean-square AOA difference. If the mean-square AOA difference is separated into the refraction and diffraction parts, the refraction part always dominates the diffraction one, and the ratio of the diffraction part to the refraction one is never larger than 0.5 for any turbulence spectrum. Based on the expressions for the mean-square AOA difference, formulae for the correlation coefficient between the angles of arrival of two counter-propagating spherical waves in atmospheric turbulence are derived. Numerical calculations are carried out by considering that the turbulence spectrum has no path dependence. It is shown that the mean-square AOA difference always approximates to the variance of AOA fluctuations. It is found that the correlation coefficient between the angles of arrival in the x or y direction of two counter-propagating spherical waves ranges from 0.46 to 0.5, implying that the instantaneous angles of arrival of two counter-propagating spherical waves in atmospheric turbulence are far from being perfectly correlated even when the turbulence spectrum does not vary along the path.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S

2016-03-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

On the equivalence of generalized least-squares approaches to the evaluation of measurement comparisons

NASA Astrophysics Data System (ADS)

Koo, A.; Clare, J. F.

2012-06-01

Analysis of CIPM international comparisons is increasingly being carried out using a model-based approach that leads naturally to a generalized least-squares (GLS) solution. While this method offers the advantages of being easier to audit and having general applicability to any form of comparison protocol, there is a lack of consensus over aspects of its implementation. Two significant results are presented that show the equivalence of three differing approaches discussed by or applied in comparisons run by Consultative Committees of the CIPM. Both results depend on a mathematical condition equivalent to the requirement that any two artefacts in the comparison are linked through a sequence of measurements of overlapping pairs of artefacts. The first result is that a GLS estimator excluding all sources of error common to all measurements of a participant is equal to the GLS estimator incorporating all sources of error, including those associated with any bias in the standards or procedures of the measuring laboratory. The second result identifies the component of uncertainty in the estimate of bias that arises from possible systematic effects in the participants' measurement standards and procedures. The expression so obtained is a generalization of an expression previously published for a one-artefact comparison with no inter-participant correlations, to one for a comparison comprising any number of repeat measurements of multiple artefacts and allowing for inter-laboratory correlations.

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

PubMed

Heddam, Salim

2014-01-01

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

Big huckleberry abundance as related to environment and associated vegetation near Mount Adams, Washington.

Treesearch

Don Minore; Michael E. Dubrasich

1978-01-01

Big huckleberry abundance was correlated with associated vegetation and soil pH in a 625-square-kilometer (241-square-mile) area southwest of Mount Adams, Washington. Annual berry production appeared to be influenced by weather more than by site factors in this area. Douglas-fir site index was not correlated with either Vaccinium membranaceum...

Least-Squares Analysis of Data with Uncertainty in "y" and "x": Algorithms in Excel and KaleidaGraph

ERIC Educational Resources Information Center

Tellinghuisen, Joel

2018-01-01

For the least-squares analysis of data having multiple uncertain variables, the generally accepted best solution comes from minimizing the sum of weighted squared residuals over all uncertain variables, with, for example, weights in x[subscript i] taken as inversely proportional to the variance [delta][subscript xi][superscript 2]. A complication…

Studies on convective heat transfer through helical coils

NASA Astrophysics Data System (ADS)

Pawar, S. S.; Sunnapwar, Vivek K.

2013-12-01

An experimental investigation on steady state convection heat transfer from vertical helical coiled tubes in water was performed for laminar flow regime. Three coils with curvature ratios as 0.0757, 0.064, 0.055 and range of Prandtl number from 3.81 to 4.8, Reynolds number from 3,166 to 9,658 were considered in this work. The heat transfer data were generated from 30 experiments conducted at constant water bath temperature (60 °C) for different cold water flow rates in helical coils. For the first time, an innovative approach of correlating Nusselt number with ‘M’ number is proposed which is not available in the literature and the developed correlations are found to be in good agreement with the work of earlier researchers. Thus, dimensionless number ‘M’ was found to be significant to characterize the hydrodynamics of fluid flow and heat transfer correlations in helical coils. Several other correlations based on experimental data are developed. To cover wide range of industrial applications, suitable generalized correlations based on extended parameters beyond the range of present experimental work are also developed. All these correlations are developed by using least-squares power law fit and multiple-regression analysis of MATLAB software. Correlations so developed were compared with published correlations and were found to be in good agreement. Comparison of heat transfer coefficients, friction factor and Nusselt number for different geometrical conditions is presented in this paper.

Monitoring multiple components in vinegar fermentation using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Soykut, Esra Acar; Boyaci, Ismail Hakki; Topcu, Ali

2013-12-15

In this study, the utility of Raman spectroscopy (RS) with chemometric methods for quantification of multiple components in the fermentation process was investigated. Vinegar, the product of a two stage fermentation, was used as a model and glucose and fructose consumption, ethanol production and consumption and acetic acid production were followed using RS and the partial least squares (PLS) method. Calibration of the PLS method was performed using model solutions. The prediction capability of the method was then investigated with both model and real samples. HPLC was used as a reference method. The results from comparing RS-PLS and HPLC with each other showed good correlations were obtained between predicted and actual sample values for glucose (R(2)=0.973), fructose (R(2)=0.988), ethanol (R(2)=0.996) and acetic acid (R(2)=0.983). In conclusion, a combination of RS with chemometric methods can be applied to monitor multiple components of the fermentation process from start to finish with a single measurement in a short time. Copyright © 2013 Elsevier Ltd. All rights reserved.

Advanced ECCD based NTM control in closed-loop operation at ASDEX Upgrade (AUG)

NASA Astrophysics Data System (ADS)

Reich, Matthias; Barrera-Orte, Laura; Behler, Karl; Bock, Alexander; Giannone, Louis; Maraschek, Marc; Poli, Emanuele; Rapson, Chris; Stober, Jörg; Treutterer, Wolfgang

2012-10-01

In high performance plasmas, Neoclassical Tearing Modes (NTMs) are regularly observed at reactor-grade beta-values. They limit the achievable normalized beta, which is undesirable because fusion performance scales as beta squared. The method of choice for controlling and avoiding NTMs at AUG is the deposition of ECCD inside the magnetic island for stabilization in real-time (rt). Our approach to tackling such complex control problems using real-time diagnostics allows rigorous optimization of all subsystems. Recent progress in rt-equilibrium reconstruction (< 3.5 ms), rt-localization of NTMs (< 8 ms) and rt beam tracing (< 25 ms) allows closed-loop feedback operation using multiple movable mirrors as the ECCD deposition actuator. The rt-equilibrium uses function parametrization or a fast Grad-Shafranov solver with an option to include rt-MSE measurements. The island localization is based on a correlation of ECE and filtered Mirnov signals. The rt beam-tracing module provides deposition locations and their derivative versus actuator position of multiple gyrotrons. The ``MHD controller'' finally drives the actuators. Results utilizing closed-loop operation with multiple gyrotrons and their effect on NTMs are shown.

A semiparametric separation curve approach for comparing correlated ROC data from multiple markers

PubMed Central

Tang, Liansheng Larry; Zhou, Xiao-Hua

2012-01-01

In this article we propose a separation curve method to identify the range of false positive rates for which two ROC curves differ or one ROC curve is superior to the other. Our method is based on a general multivariate ROC curve model, including interaction terms between discrete covariates and false positive rates. It is applicable with most existing ROC curve models. Furthermore, we introduce a semiparametric least squares ROC estimator and apply the estimator to the separation curve method. We derive a sandwich estimator for the covariance matrix of the semiparametric estimator. We illustrate the application of our separation curve method through two real life examples. PMID:23074360

Role of land-surface changes in arctic summer warming

USGS Publications Warehouse

Chapin, F. S.; Sturm, M.; Serreze, Mark C.; McFadden, J.P.; Key, J.R.; Lloyd, A.H.; McGuire, A.D.; Rupp, T.S.; Lynch, A.H.; Schimel, Joshua P.; Beringer, J.; Chapman, W.L.; Epstein, H.E.; Euskirchen, E.S.; Hinzman, L.D.; Jia, G.; Ping, C.-L.; Tape, K.D.; Thompson, C.D.C.; Walker, D.A.; Welker, J.M.

2005-01-01

A major challenge in predicting Earth's future climate state is to understand feedbacks that alter greenhouse-gas forcing. Here we synthesize field data from arctic Alaska, showing that terrestrial changes in summer albedo contribute substantially to recent high-latitude warming trends. Pronounced terrestrial summer warming in arctic Alaska correlates with a lengthening of the snow-free season that has increased atmospheric heating locally by about 3 watts per square meter per decade (similar in magnitude to the regional heating expected over multiple decades from a doubling of atmospheric CO2). The continuation of current trends in shrub and tree expansion could further amplify this atmospheric heating by two to seven times.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Early pregnancy fasting plasma glucose and lipid concentrations in pregnancy and association to offspring size: a retrospective cohort study.

PubMed

Liu, Bin; Geng, Huizhen; Yang, Juan; Zhang, Ying; Deng, Langhui; Chen, Weiqing; Wang, Zilian

2016-03-17

Hyperlipidemia and high fasting plasma glucose levels at the first prenatal visit (First Visit FPG) are both related to gestational diabetes mellitus, maternal obesity/overweight and fetal overgrowth. The purpose of the present study is to investigate the correlation between First Visit FPG and lipid concentrations, and their potential association with offspring size at delivery. Pregnant women that received regular prenatal care and delivered in our center in 2013 were recruited for the study. Fasting plasma glucose levels were tested at the first prenatal visit (First Visit FPG) and prior to delivery (Before Delivery FPG). HbA1c and lipid profiles were examined at the time of OGTT test. Maternal and neonatal clinical data were collected for analysis. Data was analyzed by independent sample t test, Pearson correlation, and Chi-square test, followed by partial correlation and multiple linear regression analyses to confirm association. Statistical significance level was α =0.05. Analyses were based on 1546 mother-baby pairs. First Visit FPG was not correlated with any lipid parameters after adjusting for maternal pregravid BMI, maternal age and gestational age at First Visit FPG. HbA1c was positively correlated with triglyceride and Apolipoprotein B in the whole cohort and in the NGT group after adjusting for maternal age and maternal BMI at OGTT test. Multiple linear regression analyses showed neonatal birth weight, head circumference and shoulder circumference were all associated with First Visit FPG and triglyceride levels. Fasting plasma glucose at first prenatal visit is not associated with lipid concentrations in mid-pregnancy, but may influence fetal growth together with triglyceride concentration.

Internet search trends analysis tools can provide real-time data on kidney stone disease in the United States.

PubMed

Willard, Scott D; Nguyen, Mike M

2013-01-01

To evaluate the utility of using Internet search trends data to estimate kidney stone occurrence and understand the priorities of patients with kidney stones. Internet search trends data represent a unique resource for monitoring population self-reported illness and health information-seeking behavior. The Google Insights for Search analysis tool was used to study searches related to kidney stones, with each search term returning a search volume index (SVI) according to the search frequency relative to the total search volume. SVIs for the term, "kidney stones," were compiled by location and time parameters and compared with the published weather and stone prevalence data. Linear regression analysis was performed to determine the association of the search interest score with known epidemiologic variations in kidney stone disease, including latitude, temperature, season, and state. The frequency of the related search terms was categorized by theme and qualitatively analyzed. The SVI correlated significantly with established kidney stone epidemiologic predictors. The SVI correlated with the state latitude (R-squared=0.25; P<.001), the state mean annual temperature (R-squared=0.24; P<.001), and state combined sex prevalence (R-squared=0.25; P<.001). Female prevalence correlated more strongly than did male prevalence (R-squared=0.37; P<.001, and R-squared=0.17; P=.003, respectively). The national SVI correlated strongly with the average U.S. temperature by month (R-squared=0.54; P=.007). The search term ranking suggested that Internet users are most interested in the diagnosis, followed by etiology, infections, and treatment. Geographic and temporal variability in kidney stone disease appear to be accurately reflected in Internet search trends data. Internet search trends data might have broader applications for epidemiologic and urologic research. Copyright © 2013 Elsevier Inc. All rights reserved.

Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system.

PubMed

Nüesch, Corina; Roos, Elena; Pagenstert, Geert; Mündermann, Annegret

2017-05-24

Inertial sensor systems are becoming increasingly popular for gait analysis because their use is simple and time efficient. This study aimed to compare joint kinematics measured by the inertial sensor system RehaGait® with those of an optoelectronic system (Vicon®) for treadmill walking and running. Additionally, the test re-test repeatability of kinematic waveforms and discrete parameters for the RehaGait® was investigated. Twenty healthy runners participated in this study. Inertial sensors and reflective markers (PlugIn Gait) were attached according to respective guidelines. The two systems were started manually at the same time. Twenty consecutive strides for walking and running were recorded and each software calculated sagittal plane ankle, knee and hip kinematics. Measurements were repeated after 20min. Ensemble means were analyzed calculating coefficients of multiple correlation for waveforms and root mean square errors (RMSE) for waveforms and discrete parameters. After correcting the offset between waveforms, the two systems/models showed good agreement with coefficients of multiple correlation above 0.950 for walking and running. RMSE of the waveforms were below 5° for walking and below 8° for running. RMSE for ranges of motion were between 4° and 9° for walking and running. Repeatability analysis of waveforms showed very good to excellent coefficients of multiple correlation (>0.937) and RMSE of 3° for walking and 3-7° for running. These results indicate that in healthy subjects sagittal plane joint kinematics measured with the RehaGait® are comparable to those using a Vicon® system/model and that the measured kinematics have a good repeatability, especially for walking. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Effect of preventive treatment on cognitive performance in patients with multiple sclerosis].

PubMed

Shorobura, Maria S

2018-01-01

Introduction: cognitive, emotional and psychopathological changes play a significant role in the clinical picture of multiple sclerosis and influence the effectiveness of drug therapy, working capacity, quality of life, and the process of rehabilitation of patients with multiple sclerosis. The aim: investigate the changes in cognitive function in patients with multiple sclerosis, such as information processing speed and working memory of patients before and after treatment with immunomodulating drug. Materials and methods:33 patients examined reliably diagnosed with multiple sclerosis who were treated with preventive examinations and treatment from 2012 to 2016. For all patients with multiple sclerosis had clinical-neurological examination (neurological status using the EDSS scale) and the cognitive status was evaluated using the PASAT auditory test. Patient screening was performed before, during and after the therapy. Statistical analysis of the results was performed in the system Statistica 8.0. We used Student's t-test (t), Mann-Whitney test (Z). Person evaluated the correlation coefficients and Spearman (r, R), Wilcoxon criterion (T), Chi-square (X²). Results: The age of patients with multiple sclerosis affects the growth and EDSS scale score decrease PASAT to treatment. Duration of illness affects the EDSS scale score and performance PASAT. Indicators PASAT not significantly decreased throughout the treatment. Conclusions: glatiramer acetate has a positive effect on cognitive function, information processing speed and working memory patients with multiple sclerosis, which is one of the important components of the therapeutic effect of this drug.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs

PubMed Central

Kim, Min-Kyu; Hong, Seong-Kwan; Kwon, Oh-Kyong

2015-01-01

This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS) applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs). The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC) with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB. PMID:26712765

Determination of the key parameters affecting historic communications satellite trends

NASA Technical Reports Server (NTRS)

Namkoong, D.

1984-01-01

Data representing 13 series of commercial communications satellites procured between 1968 and 1982 were analyzed to determine the factors that have contributed to the general reduction over time of the per circuit cost of communications satellites. The model by which the data were analyzed was derived from a general telecommunications application and modified to be more directly applicable for communications satellites. In this model satellite mass, bandwidth-years, and technological change were the variable parameters. A linear, least squares, multiple regression routine was used to obtain the measure of significance of the model. Correlation was measured by coefficient of determination (R super 2) and t-statistic. The results showed that no correlation could be established with satellite mass. Bandwidth-year however, did show a significant correlation. Technological change in the bandwidth-year case was a significant factor in the model. This analysis and the conclusions derived are based on mature technologies, i.e., satellite designs that are evolutions of earlier designs rather than the first of a new generation. The findings, therefore, are appropriate to future satellites only if they are a continuation of design evolution.

Imaging of downward-looking linear array SAR using three-dimensional spatial smoothing MUSIC algorithm

NASA Astrophysics Data System (ADS)

Zhang, Siqian; Kuang, Gangyao

2014-10-01

In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

Factors influencing the academic motivation of individual college students.

PubMed

Yoshida, Masahiro; Tanaka, Masaaki; Mizuno, Kei; Ishii, Akira; Nozaki, Kumi; Urakawa, Ayako; Cho, Yuki; Kataoka, Yosky; Watanabe, Yasuyoshi

2008-10-01

Motivation is an important psychological concept in academic learning. Subjects performed jigsaw puzzle and square puzzle sessions (as difficulty variant task) and 80%, 50%, and 20% completion sessions (as completion variant task). After square puzzle or 20% completion sessions, subjective motivation decreased. Although baseline scores on an academic motivation scale were negatively correlated with changes in subjective motivation for the square puzzle session, a positive correlation was observed for the 20% completion session. These suggest that while continual completion of facile task trials may support the motivation of college students with lower academic motivation, attempting difficult task trials may sustain that of those with higher academic motivation.

Confirmatory factor analysis of the female sexual function index.

PubMed

Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

2013-01-01

The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column.

PubMed

Markopoulou, Catherine K; Kouskoura, Maria G; Koundourellis, John E

2011-06-01

Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in telomere length will require further investigation regarding biological influence of exposure. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Load forecasting via suboptimal seasonal autoregressive models and iteratively reweighted least squares estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mbamalu, G.A.N.; El-Hawary, M.E.

The authors propose suboptimal least squares or IRWLS procedures for estimating the parameters of a seasonal multiplicative AR model encountered during power system load forecasting. The proposed method involves using an interactive computer environment to estimate the parameters of a seasonal multiplicative AR process. The method comprises five major computational steps. The first determines the order of the seasonal multiplicative AR process, and the second uses the least squares or the IRWLS to estimate the optimal nonseasonal AR model parameters. In the third step one obtains the intermediate series by back forecast, which is followed by using the least squaresmore » or the IRWLS to estimate the optimal season AR parameters. The final step uses the estimated parameters to forecast future load. The method is applied to predict the Nova Scotia Power Corporation's 168 lead time hourly load. The results obtained are documented and compared with results based on the Box and Jenkins method.« less

GIS-based spatial statistical analysis of risk areas for liver flukes in Surin Province of Thailand.

PubMed

Rujirakul, Ratana; Ueng-arporn, Naporn; Kaewpitoon, Soraya; Loyd, Ryan J; Kaewthani, Sarochinee; Kaewpitoon, Natthawut

2015-01-01

It is urgently necessary to be aware of the distribution and risk areas of liver fluke, Opisthorchis viverrini, for proper allocation of prevention and control measures. This study aimed to investigate the human behavior, and environmental factors influencing the distribution in Surin Province of Thailand, and to build a model using stepwise multiple regression analysis with a geographic information system (GIS) on environment and climate data. The relationship between the human behavior, attitudes (<50%; X111), environmental factors like population density (148-169 pop/km2; X73), and land use as wetland (X64), were correlated with the liver fluke disease distribution at 0.000, 0.034, and 0.006 levels, respectively. Multiple regression analysis, by equations OV=-0.599+0.005(population density (148-169 pop/km2); X73)+0.040 (human attitude (<50%); X111)+0.022 (land used (wetland; X64), was used to predict the distribution of liver fluke. OV is the patients of liver fluke infection, R Square=0.878, and, Adjust R Square=0.849. By GIS analysis, we found Si Narong, Sangkha, Phanom Dong Rak, Mueang Surin, Non Narai, Samrong Thap, Chumphon Buri, and Rattanaburi to have the highest distributions in Surin province. In conclusion, the combination of GIS and statistical analysis can help simulate the spatial distribution and risk areas of liver fluke, and thus may be an important tool for future planning of prevention and control measures.

Plasma S100β is not a useful biomarker for tumor burden in neurofibromatosis.

PubMed

Smith, Miriam J; Esparza, Sonia; Merker, Vanessa L; Muzikansky, Alona; Bredella, Miriam A; Harris, Gordon J; Kassarjian, Ara; Cai, Wenli; Walker, James A; Mautner, Victor F; Plotkin, Scott R

2013-05-01

Neurofibromatosis 1 (NF1), NF2, and schwannomatosis are characterized by a predisposition to develop multiple neurofibromas and schwannomas. Currently, there is no blood test to estimate tumor burden in patients with these disorders. We explored whether S100β would act as a biomarker of tumor burden in NF since S100β is a classic immunohistochemical marker of astrocytes, oligodendrocytes and Schwann cells and a small study showed S100β concentrations correlate with the volume of vestibular schwannomas. We calculated whole-body tumor burden in subjects with NF1, NF2, and schwannomatosis using whole-body MRI (WBMRI) and measured the concentration of S100β in plasma using ELISA. We used chi-square tests and Spearman rank correlations to test the relationship between S100β levels and whole-body tumor burden. 127 consecutive patients were enrolled in the study (69 NF1 patients, 28 NF2 patients, and 30 schwannomatosis patients). The median age was 40years, 43% were male, and median whole-body tumor volume was 26.9mL. There was no relationship between the presence of internal tumors and the presence of detectable S100β in blood for the overall group or for individual diagnoses (p>0.05 by chi-square for all comparisons). Similarly, there was no correlation between whole-body tumor volume and S100β concentration for the overall group or for individual diagnoses (p>0.05 by Spearman for all comparisons). Plasma S100β is not a useful biomarker for tumor burden in the neurofibromatoses. Further work is needed to identify a reliable biomarker of tumor burden in NF patients. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Mapping Environmental Inequalities Relevant for Health for Informing Urban Planning Interventions-A Case Study in the City of Dortmund, Germany.

PubMed

Flacke, Johannes; Schüle, Steffen Andreas; Köckler, Heike; Bolte, Gabriele

2016-07-13

Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population.

Mapping Environmental Inequalities Relevant for Health for Informing Urban Planning Interventions—A Case Study in the City of Dortmund, Germany

PubMed Central

Flacke, Johannes; Schüle, Steffen Andreas; Köckler, Heike; Bolte, Gabriele

2016-01-01

Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population. PMID:27420090

A reduced factor structure for the PROQOL-HIV questionnaire provided reliable indicators of health-related quality of life.

PubMed

Lalanne, Christophe; Chassany, Olivier; Carrieri, Patrizia; Marcellin, Fabienne; Armstrong, Andrew R; Lert, France; Spire, Bruno; Dray-Spira, Rosemary; Duracinsky, Martin

2016-04-01

To identify a simplified factor structure for the PROQOL-human immunodeficiency virus (HIV) questionnaire to improve the measurement of the health-related quality of life (HRQL) of HIV-positive patients in clinical care and research settings. HRQL data were collected using the eight-dimension PROQOL-HIV questionnaire from 2,537 patients (VESPA2 study). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) validated a simpler four-factor structure and assessed measurement invariance (MI). Multigroup analysis assessed the effect of sex, age, and antiretroviral therapy (ART) on the resulting factor scores. Correlations with symptom and Short Form (SF)-12 self-reports assessed convergent validity. Item analysis, EFA, and CFAs confirmed the validity [comparative fit index (CFI), 0.948; root mean square error of approximation, 0.064] and reliability (α's ≥ 0.8) of four dimensions: physical health and symptoms, health concerns and mental distress, social and intimate relationships, and treatment-related impact. Strong MI was demonstrated across sex and age (decrease in CFI <0.01). A multiple-cause multiple-indicator model indicated that HRQL correlated as expected with sex, age, and the ART status. Correlations of HRQL, symptom reports, and SF-12 scores evidenced convergent validity criterion. The simplified factor structure and scoring scheme for PROQOL-HIV will allow clinicians to monitor with greater reliability the HRQL of patients in clinical care and research settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.

PubMed

Rajan, Jeny; Veraart, Jelle; Van Audekerke, Johan; Verhoye, Marleen; Sijbers, Jan

2012-12-01

Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. Copyright © 2012 Elsevier Inc. All rights reserved.

A proposed study of multiple scattering through clouds up to 1 THz

NASA Technical Reports Server (NTRS)

Gerace, G. C.; Smith, E. K.

1992-01-01

A rigorous computation of the electromagnetic field scattered from an atmospheric liquid water cloud is proposed. The recent development of a fast recursive algorithm (Chew algorithm) for computing the fields scattered from numerous scatterers now makes a rigorous computation feasible. A method is presented for adapting this algorithm to a general case where there are an extremely large number of scatterers. It is also proposed to extend a new binary PAM channel coding technique (El-Khamy coding) to multiple levels with non-square pulse shapes. The Chew algorithm can be used to compute the transfer function of a cloud channel. Then the transfer function can be used to design an optimum El-Khamy code. In principle, these concepts can be applied directly to the realistic case of a time-varying cloud (adaptive channel coding and adaptive equalization). A brief review is included of some preliminary work on cloud dispersive effects on digital communication signals and on cloud liquid water spectra and correlations.

Long-term care planning and preparation among persons with multiple sclerosis.

PubMed

Putnam, Michelle; Tang, Fengyan

2008-01-01

Individuals with multiple sclerosis (MS) primarily rely on informal supports such as family members and assistive technology to meet their daily needs. As they age, formal supports may become important to compliment these supports and sustain community-based living. No previous research exists exploring plans and preparations of persons with MS for future independent living and long-term care needs. We analyzed data from a random sample survey (N = 580) to assess knowledge and perceptions of future service needs using ANOVA, chi-square, correlations, and MANOVA procedures. Results indicate that overall, most respondents are not well informed and have not planned or prepared for future care needs. Persons reporting severe MS were more likely to plan and prepare. Key "entry points" for making preparations include receiving specific education and planning information, discussions with family and professional service providers, and increased age, education, and income. We recommend greater infusion of long-term care planning into these existing entry points and creation of new entry points including healthcare provides and insurers.

Costas loop lock detection in the advanced receiver

NASA Technical Reports Server (NTRS)

Mileant, A.; Hinedi, S.

1989-01-01

The advanced receiver currently being developed uses a Costas digital loop to demodulate the subcarrier. Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between the samples of the phase-error process. Accounting for this correlation is necessary to achieve the desired lock-detection probability for a given false-alarm rate. Both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the square-law and the absolute-value type detectors. Results are obtained which depict the lock-detection probability as a function of loop signal-to-noise ratio for a given false-alarm rate. The mathematical model and computer simulation show that the square-law detector experiences less degradation due to phase jitter than the absolute-value detector and that the degradation in detector signal-to-noise ratio is more pronounced for square-wave than for sine-wave signals.

Allowing for Correlations between Correlations in Random-Effects Meta-Analysis of Correlation Matrices

ERIC Educational Resources Information Center

Prevost, A. Toby; Mason, Dan; Griffin, Simon; Kinmonth, Ann-Louise; Sutton, Stephen; Spiegelhalter, David

2007-01-01

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of…

Assessing the statistical robustness of inter- and intra-basinal carbon isotope chemostratigraphic correlation

NASA Astrophysics Data System (ADS)

Hay, C.; Creveling, J. R.; Huybers, P. J.

2016-12-01

Excursions in the stable carbon isotopic composition of carbonate rocks (δ13Ccarb) can facilitate correlation of Precambrian and Phanerozoic sedimentary successions at a higher temporal resolution than radiometric and biostratigraphic frameworks typically afford. Within the bounds of litho- and biostratigraphic constraints, stratigraphers often correlate isotopic patterns between distant stratigraphic sections through visual alignment of local maxima and minima of isotopic values. The reproducibility of this method can prove challenging and, thus, evaluating the statistical robustness of intrabasinal composite carbon isotope curves, and global correlations to these reference curves, remains difficult. To assess the reproducibility of stratigraphic alignment of δ13Ccarb data, and correlations between carbon isotope excursions, we employ a numerical dynamic time warping methodology that stretches and squeezes the time axis of a record to obtain an optimal correlation (in a least-squares sense) between time-uncertain series of data. In particular, we assess various alignments between series of Early Cambrian δ13Ccarb data with respect to plausible matches. We first show that an alignment of these records obtained visually, and published previously, is broadly reproducible using dynamic time warping. Alternative alignments with similar goodness of fits are also obtainable, and their stratigraphic plausibility are discussed. This approach should be generalizable to an algorithm for the purposes of developing a library of plausible alignments between multiple time-uncertain stratigraphic records.

MRI-based intelligence quotient (IQ) estimation with sparse learning.

PubMed

Wang, Liye; Wee, Chong-Yaw; Suk, Heung-Il; Tang, Xiaoying; Shen, Dinggang

2015-01-01

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject's IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge.

Percolation thresholds and fractal dimensions for square and cubic lattices with long-range correlated defects

NASA Astrophysics Data System (ADS)

Zierenberg, Johannes; Fricke, Niklas; Marenz, Martin; Spitzner, F. P.; Blavatska, Viktoria; Janke, Wolfhard

2017-12-01

We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as a function of the correlation strength. The correlations are generated using a discrete version of the Fourier filtering method. We consider two different metrics to set the length scales over which the correlations decay, showing that the percolation thresholds are highly sensitive to such system details. By contrast, we verify that the fractal dimension df is a universal quantity and unaffected by the choice of metric. We also show that for weak correlations, its value coincides with that for the uncorrelated system. In two dimensions we observe a clear increase of the fractal dimension with increasing correlation strength, approaching df→2 . The onset of this change does not seem to be determined by the extended Harris criterion.

Reliability and Concurrent Validity of the Narrow Path Walking Test in Persons With Multiple Sclerosis.

PubMed

Rosenblum, Uri; Melzer, Itshak

2017-01-01

About 90% of people with multiple sclerosis (PwMS) have gait instability and 50% fall. Reliable and clinically feasible methods of gait instability assessment are needed. The study investigated the reliability and validity of the Narrow Path Walking Test (NPWT) under single-task (ST) and dual-task (DT) conditions for PwMS. Thirty PwMS performed the NPWT on 2 different occasions, a week apart. Number of Steps, Trial Time, Trial Velocity, Step Length, Number of Step Errors, Number of Cognitive Task Errors, and Number of Balance Losses were measured. Intraclass correlation coefficients (ICC2,1) were calculated from the average values of NPWT parameters. Absolute reliability was quantified from standard error of measurement (SEM) and smallest real difference (SRD). Concurrent validity of NPWT with Functional Reach Test, Four Square Step Test (FSST), 12-item Multiple Sclerosis Walking Scale (MSWS-12), and 2 Minute Walking Test (2MWT) was determined using partial correlations. Intraclass correlation coefficients (ICCs) for most NPWT parameters during ST and DT ranged from 0.46-0.94 and 0.55-0.95, respectively. The highest relative reliability was found for Number of Step Errors (ICC = 0.94 and 0.93, for ST and DT, respectively) and Trial Velocity (ICC = 0.83 and 0.86, for ST and DT, respectively). Absolute reliability was high for Number of Step Errors in ST (SEM % = 19.53%) and DT (SEM % = 18.14%) and low for Trial Velocity in ST (SEM % = 6.88%) and DT (SEM % = 7.29%). Significant correlations for Number of Step Errors and Trial Velocity were found with FSST, MSWS-12, and 2MWT. In persons with PwMS performing the NPWT, Number of Step Errors and Trial Velocity were highly reliable parameters. Based on correlations with other measures of gait instability, Number of Step Errors was the most valid parameter of dynamic balance under the conditions of our test.Video Abstract available for more insights from the authors (see Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A159).

Application of Partial Least Square (PLS) Regression to Determine Landscape-Scale Aquatic Resources Vulnerability in the Ozark Mountains

EPA Science Inventory

Partial least squares (PLS) analysis offers a number of advantages over the more traditionally used regression analyses applied in landscape ecology, particularly for determining the associations among multiple constituents of surface water and landscape configuration. Common dat...

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

PubMed

Heddam, Salim

2014-11-01

The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

On estimating gravity anomalies - A comparison of least squares collocation with conventional least squares techniques

NASA Technical Reports Server (NTRS)

Argentiero, P.; Lowrey, B.

1977-01-01

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

On estimating gravity anomalies: A comparison of least squares collocation with least squares techniques

NASA Technical Reports Server (NTRS)

Argentiero, P.; Lowrey, B.

1976-01-01

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described, and its numerical properties are compared with the numerical properties of the conventional least squares estimator.

Dedicated Space | Poster

Cancer.gov

The three-story, 330,000-square-foot Advanced Technology Research Facility has nearly 40,000 square feet designated as partnership space (shown in blue) for co-location of collaborators from industry, academia, nonprofit sectors, and other government agencies. The partnership space, combined with multiple conference rooms and meeting areas, encourages both internal and

Dedicated Space | Poster

Cancer.gov

The three-story, 330,000-square-foot Advanced Technology Research Facility has nearly 40,000 square feet designated as partnership space (shown in blue) for co-location of collaborators from industry, academia, nonprofit sectors, and other government agencies. The partnership space, combined with multiple conference rooms and meeting areas, encourages both internal and external collaborations.

Multi-element array signal reconstruction with adaptive least-squares algorithms

NASA Technical Reports Server (NTRS)

Kumar, R.

1992-01-01

Two versions of the adaptive least-squares algorithm are presented for combining signals from multiple feeds placed in the focal plane of a mechanical antenna whose reflector surface is distorted due to various deformations. Coherent signal combining techniques based on the adaptive least-squares algorithm are examined for nearly optimally and adaptively combining the outputs of the feeds. The performance of the two versions is evaluated by simulations. It is demonstrated for the example considered that both of the adaptive least-squares algorithms are capable of offsetting most of the loss in the antenna gain incurred due to reflector surface deformations.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

Prevalence and Correlates of Tobacco and Nicotine Containing Product Use in a Sample of United States Air Force Trainees

PubMed Central

Derefinko, Karen J.; Bursac, Zoran; Ebbert, Jon O.; Colvin, Lauren; Talcott, Gerald W.; Hryshko-Mullen, Ann S.; Richey, Phyllis A.; Klesges, Robert C.

2016-01-01

Introduction: Although there is increasing attention to the prevalence of new and emerging tobacco products in the civilian population, remarkably little is known about the current prevalence of these products in a military population. Methods: The current investigation was designed to determine the prevalence of tobacco and nicotine containing products (TNCP) and correlates of use across multiple cohorts of trainees undergoing Technical Training in the US Air Force between April 2013 and December 2014. Chi-square test, Cochran–Armitage test for linear trend, and logistic regression models were applied to test differences and linear trends across time for TNCP use as well as correlates of use in a cross-sectional sample of 13 685 Airmen (final analytic sample). Results: Over a quarter (26.9%) of Airmen reported regular use of a TNCP. The two most prevalent products were cigarettes (11.2%) and hookah (10.5%). Among correlates of use, Airmen that regularly use TNCPs were more likely to be male, younger, non-Hispanic white, and single with a high school degree or General Education Development. Hookah was the most endorsed for intentions to use, and along with e-cigarettes, had the lowest perception of harm. While prevalence of most products remained constant across entering cohorts, the prevalence of e-cigarettes showed significant linear increase. Conclusions: The prevalence of TNCP use is high across cohorts of Airmen. Remarkably high estimates of future intentions to use and low perceptions of harm for emerging products suggest that intervention efforts should be directed at multiple forms of TNCP use to address this important public health issue. PMID:25895952

Channel Acquisition for Massive MIMO-OFDM With Adjustable Phase Shift Pilots

NASA Astrophysics Data System (ADS)

You, Li; Gao, Xiqi; Swindlehurst, A. Lee; Zhong, Wen

2016-03-01

We propose adjustable phase shift pilots (APSPs) for channel acquisition in wideband massive multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) to reduce the pilot overhead. Based on a physically motivated channel model, we first establish a relationship between channel space-frequency correlations and the channel power angle-delay spectrum in the massive antenna array regime, which reveals the channel sparsity in massive MIMO-OFDM. With this channel model, we then investigate channel acquisition, including channel estimation and channel prediction, for massive MIMO-OFDM with APSPs. We show that channel acquisition performance in terms of sum mean square error can be minimized if the user terminals' channel power distributions in the angle-delay domain can be made non-overlapping with proper phase shift scheduling. A simplified pilot phase shift scheduling algorithm is developed based on this optimal channel acquisition condition. The performance of APSPs is investigated for both one symbol and multiple symbol data models. Simulations demonstrate that the proposed APSP approach can provide substantial performance gains in terms of achievable spectral efficiency over the conventional phase shift orthogonal pilot approach in typical mobility scenarios.

Uplink transmit beamforming design for SINR maximization with full multiuser channel state information

NASA Astrophysics Data System (ADS)

Xi, Songnan; Zoltowski, Michael D.

2008-04-01

Multiuser multiple-input multiple-output (MIMO) systems are considered in this paper. We continue our research on uplink transmit beamforming design for multiple users under the assumption that the full multiuser channel state information, which is the collection of the channel state information between each of the users and the base station, is known not only to the receiver but also to all the transmitters. We propose an algorithm for designing optimal beamforming weights in terms of maximizing the signal-to-interference-plus-noise ratio (SINR). Through statistical modeling, we decouple the original mathematically intractable optimization problem and achieved a closed-form solution. As in our previous work, the minimum mean-squared error (MMSE) receiver with successive interference cancellation (SIC) is adopted for multiuser detection. The proposed scheme is compared with an existing jointly optimized transceiver design, referred to as the joint transceiver in this paper, and our previously proposed eigen-beamforming algorithm. Simulation results demonstrate that our algorithm, with much less computational burden, accomplishes almost the same performance as the joint transceiver for spatially independent MIMO channel and even better performance for spatially correlated MIMO channels. And it always works better than our previously proposed eigen beamforming algorithm.

Effect of pH Test-Strip Characteristics on Accuracy of Readings.

PubMed

Metheny, Norma A; Gunn, Emily M; Rubbelke, Cynthia S; Quillen, Terrilynn Fox; Ezekiel, Uthayashanker R; Meert, Kathleen L

2017-06-01

Little is known about characteristics of colorimetric pH test strips that are most likely to be associated with accurate interpretations in clinical situations. To compare the accuracy of 4 pH test strips with varying characteristics (ie, multiple vs single colorimetric squares per calibration, and differing calibration units [1.0 vs 0.5]). A convenience sample of 100 upper-level nursing students with normal color vision was recruited to evaluate the accuracy of the test strips. Six buffer solutions (pH range, 3.0 to 6.0) were used during the testing procedure. Each of the 100 participants performed 20 pH tests in random order, providing a total of 2000 readings. The sensitivity and specificity of each test strip was computed. In addition, the degree to which the test strips under- or overestimated the pH values was analyzed using descriptive statistics. Our criterion for correct readings was an exact match with the pH buffer solution being evaluated. Although none of the test strips evaluated in our study was 100% accurate at all of the measured pH values, those with multiple squares per pH calibration were clearly superior overall to those with a single test square. Test strips with multiple squares per calibration were associated with greater overall accuracy than test strips with a single square per calibration. However, because variable degrees of error were observed in all of the test strips, use of a pH meter is recommended when precise readings are crucial. ©2017 American Association of Critical-Care Nurses.

CARS Spectral Fitting with Multiple Resonant Species using Sparse Libraries

NASA Technical Reports Server (NTRS)

Cutler, Andrew D.; Magnotti, Gaetano

2010-01-01

The dual pump CARS technique is often used in the study of turbulent flames. Fast and accurate algorithms are needed for fitting dual-pump CARS spectra for temperature and multiple chemical species. This paper describes the development of such an algorithm. The algorithm employs sparse libraries, whose size grows much more slowly with number of species than a conventional library. The method was demonstrated by fitting synthetic "experimental" spectra containing 4 resonant species (N2, O2, H2 and CO2), both with noise and without it, and by fitting experimental spectra from a H2-air flame produced by a Hencken burner. In both studies, weighted least squares fitting of signal, as opposed to least squares fitting signal or square-root signal, was shown to produce the least random error and minimize bias error in the fitted parameters.

Correlation of Electropenetrography Waveforms From Lygus lineolaris (Hemiptera: Miridae) Feeding on Cotton Squares With Chemical Evidence of Inducible Tannins.

PubMed

Cervantes, Felix A; Backus, Elaine A; Godfrey, Larry; Wallis, Christopher; Akbar, Waseem; Clark, Thomas L; Rojas, Maria G

2017-10-01

Probing behavior of Lygus lineolaris (Palisot de Beauvois) has previously been characterized with electropenetrography (EPG). Cell rupturing (CR) and ingestion (I) EPG waveforms were identified as the two main stylet-probing behaviors by adult L. lineolaris. However, characterization and identification of EPG waveforms are not complete until specific events of a particular waveform are correlated to insect probing. With the use of EPG, histology, microscopy, and chemical analysis, probing behavior of L. lineolaris on pin-head cotton squares was studied. Occurrences of waveforms CR and I were artificially terminated during the EPG recording. Histological samples of probed cotton squares were prepared and analyzed to correlate specific types and occurrences of feeding damage location and plant responses to insect feeding. Both CR and I occurred in the staminal column of the cotton square. Cell rupturing events elicited the production of dark-red deposits seen in histological staining that were demonstrated via chemical analysis to contain condensed tannins. We hypothesize that wounding and saliva secreted during CR triggered release of tannins, because tannin production was positively correlated with the number of probes with single CR events performed by L. lineolaris. Degraded plant tissue and tannins were removed from the staminal column during occurrence of waveform I. These results conclude the process of defining CR and I as probing waveforms performed by L. lineolaris on pin-head cotton squares. These biological definitions will now allow EPG to be used to quantitatively compare L. lineolaris feeding among different plant treatments, with the goal of improving pest management tactics against this pest. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Stability of phases of a square-well fluid within superposition approximation

NASA Astrophysics Data System (ADS)

Piasecki, Jarosław; Szymczak, Piotr; Kozak, John J.

2013-04-01

The analytic and numerical methods introduced previously to study the phase behavior of hard sphere fluids starting from the Yvon-Born-Green (YBG) equation under the Kirkwood superposition approximation (KSA) are adapted to the square-well fluid. We are able to show conclusively that the YBG equation under the KSA closure when applied to the square-well fluid: (i) predicts the existence of an absolute stability limit corresponding to freezing where undamped oscillations appear in the long-distance behavior of correlations, (ii) in accordance with earlier studies reveals the existence of a liquid-vapor transition by the appearance of a "near-critical region" where monotonically decaying correlations acquire very long range, although the system never loses stability.

Resolving the Impact of Biological Processes on Water Transport in Unsaturated Porous Media Through Nuclear Magnetic Resonance Micro-Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seymour, Joseph D.

2005-06-01

The magnetic resonance microscopy (MRM) work at Montana State University has extended the imaging of a single biofilm in a 1 mm capillary reactor to correlate T2 magnetic relaxation maps displaying biofilm structure with the corresponding velocity patterns in three dimensions in a Staphylococcus epidermidis biofilm fouled square capillary. A square duct geometry is chosen to provide correlation with existing experiments and simulations, as research bioreactors tend to be of square or rectangular cross section for optical or microelectrode access. The spatially resolved velocity data provide details on the impact of biofilm induced advection on mass transport from the bulkmore » fluid to the biofilm and through the capillary bioreactor.« less

Influence of educational status and other variables on HIV risk perception among military personnel: A large cohort finding

PubMed Central

Essien, E. James; Ogungbade, Gbadebo O.; Ward, Doriel; Ekong, Ernest; Ross, Michael W.; Meshack, Angela; Holmes, Laurens

2007-01-01

HIV risk perception remains an effective determinant of HIV transmission. Although higher educational attainment has been associated with increased HIV risk perception, this predictor remains to be assessed among Nigerian military personnel (NMP). In a prospective cohort of 2,213 NMP, the effect of education and other factors on HIV risk perception were assessed at baseline using chi square statistic and unconditional logistic regression. There was an inverse correlation between higher educational attainment and HIV risk perception in the univarible model, prevalence odds ratio (POR), 0.64, 95% confidence interval (CI) = 0.52–0.79. This association persisted after adjustment for relevant covariates in the multivariable model (POR, 0.70, 95% CI=0.56–0.88). Likewise, there was a direct correlation between use of alcohol and marijuana and HIV risk perception (p <0.05). In contrast, casual sex and gender were not statistically significantly associated with HIV risk perception, P >0.05. This study is indicative of an inverse correlation between educational attainment and HIV risk perception, as well as a direct correlation between alcohol and marijuana and HIV risk perception among NMP. Therefore HIV prevention interventions targeted at NMP need to include multiple factors that may impact on risk perception regardless of educational status of the participants. PMID:18062392

Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5.

PubMed

Cho, Hyun; Kwon, Min; Choi, Ji-Hye; Lee, Sang-Kyu; Choi, Jung Seok; Choi, Sam-Wook; Kim, Dai-Jin

2014-09-01

This study was conducted to develop and validate a standardized self-diagnostic Internet addiction (IA) scale based on the diagnosis criteria for Internet Gaming Disorder (IGD) in the Diagnostic and Statistical Manual of Mental Disorder, 5th edition (DSM-5). Items based on the IGD diagnosis criteria were developed using items of the previous Internet addiction scales. Data were collected from a community sample. The data were divided into two sets, and confirmatory factor analysis (CFA) was performed repeatedly. The model was modified after discussion with professionals based on the first CFA results, after which the second CFA was performed. The internal consistency reliability was generally good. The items that showed significantly low correlation values based on the item-total correlation of each factor were excluded. After the first CFA was performed, some factors and items were excluded. Seven factors and 26 items were prepared for the final model. The second CFA results showed good general factor loading, Squared Multiple Correlation (SMC) and model fit. The model fit of the final model was good, but some factors were very highly correlated. It is recommended that some of the factors be refined through further studies. Copyright © 2014. Published by Elsevier Ltd.

Building on crossvalidation for increasing the quality of geostatistical modeling

USGS Publications Warehouse

Olea, R.A.

2012-01-01

The random function is a mathematical model commonly used in the assessment of uncertainty associated with a spatially correlated attribute that has been partially sampled. There are multiple algorithms for modeling such random functions, all sharing the requirement of specifying various parameters that have critical influence on the results. The importance of finding ways to compare the methods and setting parameters to obtain results that better model uncertainty has increased as these algorithms have grown in number and complexity. Crossvalidation has been used in spatial statistics, mostly in kriging, for the analysis of mean square errors. An appeal of this approach is its ability to work with the same empirical sample available for running the algorithms. This paper goes beyond checking estimates by formulating a function sensitive to conditional bias. Under ideal conditions, such function turns into a straight line, which can be used as a reference for preparing measures of performance. Applied to kriging, deviations from the ideal line provide sensitivity to the semivariogram lacking in crossvalidation of kriging errors and are more sensitive to conditional bias than analyses of errors. In terms of stochastic simulation, in addition to finding better parameters, the deviations allow comparison of the realizations resulting from the applications of different methods. Examples show improvements of about 30% in the deviations and approximately 10% in the square root of mean square errors between reasonable starting modelling and the solutions according to the new criteria. ?? 2011 US Government.

A regression-kriging model for estimation of rainfall in the Laohahe basin

NASA Astrophysics Data System (ADS)

Wang, Hong; Ren, Li L.; Liu, Gao H.

2009-10-01

This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS), which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression (MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and where topography has a major influence on rainfall.

Weighted partial least squares based on the error and variance of the recovery rate in calibration set.

PubMed

Yu, Shaohui; Xiao, Xue; Ding, Hong; Xu, Ge; Li, Haixia; Liu, Jing

2017-08-05

The quantitative analysis is very difficult for the emission-excitation fluorescence spectroscopy of multi-component mixtures whose fluorescence peaks are serious overlapping. As an effective method for the quantitative analysis, partial least squares can extract the latent variables from both the independent variables and the dependent variables, so it can model for multiple correlations between variables. However, there are some factors that usually affect the prediction results of partial least squares, such as the noise, the distribution and amount of the samples in calibration set etc. This work focuses on the problems in the calibration set that are mentioned above. Firstly, the outliers in the calibration set are removed by leave-one-out cross-validation. Then, according to two different prediction requirements, the EWPLS method and the VWPLS method are proposed. The independent variables and dependent variables are weighted in the EWPLS method by the maximum error of the recovery rate and weighted in the VWPLS method by the maximum variance of the recovery rate. Three organic matters with serious overlapping excitation-emission fluorescence spectroscopy are selected for the experiments. The step adjustment parameter, the iteration number and the sample amount in the calibration set are discussed. The results show the EWPLS method and the VWPLS method are superior to the PLS method especially for the case of small samples in the calibration set. Copyright © 2017 Elsevier B.V. All rights reserved.

DETECTION OF FAST RADIO TRANSIENTS WITH MULTIPLE STATIONS: A CASE STUDY USING THE VERY LONG BASELINE ARRAY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, David R.; Wagstaff, Kiri L.; Majid, Walid A.

2011-07-10

Recent investigations reveal an important new class of transient radio phenomena that occur on submillisecond timescales. Often, transient surveys' data volumes are too large to archive exhaustively. Instead, an online automatic system must excise impulsive interference and detect candidate events in real time. This work presents a case study using data from multiple geographically distributed stations to perform simultaneous interference excision and transient detection. We present several algorithms that incorporate dedispersed data from multiple sites, and report experiments with a commensal real-time transient detection system on the Very Long Baseline Array. We test the system using observations of pulsar B0329+54.more » The multiple-station algorithms enhanced sensitivity for detection of individual pulses. These strategies could improve detection performance for a future generation of geographically distributed arrays such as the Australian Square Kilometre Array Pathfinder and the Square Kilometre Array.« less

Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Miner Haygood, Tamara; Park, Subok

2018-02-01

Model observers are widely used in task-based assessments of medical image quality. The presence of multiple abnormalities in a single set of images, such as in multifocal multicentric breast cancer (MFMC), has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors. However, prior studies of DBT image quality all focus on unifocal breast cancers. In this study, we extended our 2D multi-lesion (ML) channelized Hotelling observer (CHO) into a 3D ML-CHO that detects multiple lesions from volumetric imaging data. Then we employed the 3D ML-CHO to identify optimal DBT acquisition geometries for detection of MFMC. Digital breast phantoms with multiple embedded synthetic lesions were scanned by simulated DBT scanners of different geometries (wide/narrow angular span, different number of projections per scan) to simulate MFMC cases. With new implementations of 3D partial least squares (PLS) and modified Laguerre-Gauss (LG) channels, the 3D ML-CHO made detection decisions based upon the overall information from individual DBT slices and their correlations. Our evaluation results show that: (1) the 3D ML-CHO could achieve good detection performance with a small number of channels, and 3D PLS channels on average outperform the counterpart LG channels; (2) incorporating locally varying anatomical backgrounds and their correlations as in the 3D ML-CHO is essential for multi-lesion detection; (3) the most effective DBT geometry for detection of MFMC may vary when the task of clinical interest changes, and a given DBT geometry may not yield images that are equally informative for detecting MF, MC, and unifocal cancers.

The Construction of a Square through Multiple Approaches to Foster Learners' Mathematical Thinking

ERIC Educational Resources Information Center

Reyes-Rodriguez, Aaron; Santos-Trigo, Manuel; Barrera-Mora, Fernando

2017-01-01

The task of constructing a square is used to argue that looking for and pursuing several solution routes is a powerful principle to identify and analyse properties of mathematical objects, to understand problem statements and to engage in mathematical thinking activities. Developing mathematical understanding requires that students delve into…

The Problems of Multiple Feedback Estimation.

ERIC Educational Resources Information Center

Bulcock, Jeffrey W.

The use of two-stage least squares (2SLS) for the estimation of feedback linkages is inappropriate for nonorthogonal data sets because 2SLS is extremely sensitive to multicollinearity. It is argued that what is needed is use of a different estimating criterion than the least squares criterion. Theoretically the variance normalization criterion has…

A parallel algorithm for computing the eigenvalues of a symmetric tridiagonal matrix

NASA Technical Reports Server (NTRS)

Swarztrauber, Paul N.

1993-01-01

A parallel algorithm, called polysection, is presented for computing the eigenvalues of a symmetric tridiagonal matrix. The method is based on a quadratic recurrence in which the characteristic polynomial is constructed on a binary tree from polynomials whose degree doubles at each level. Intervals that contain exactly one zero are determined by the zeros of polynomials at the previous level which ensures that different processors compute different zeros. The signs of the polynomials at the interval endpoints are determined a priori and used to guarantee that all zeros are found. The use of finite-precision arithmetic may result in multiple zeros; however, in this case, the intervals coalesce and their number determines exactly the multiplicity of the zero. For an N x N matrix the eigenvalues can be determined in O(log-squared N) time with N-squared processors and O(N) time with N processors. The method is compared with a parallel variant of bisection that requires O(N-squared) time on a single processor, O(N) time with N processors, and O(log N) time with N-squared processors.

A New Method of Using Sensor Arrays for Gas Leakage Location Based on Correlation of the Time-Space Domain of Continuous Ultrasound

PubMed Central

Bian, Xu; Zhang, Yu; Li, Yibo; Gong, Xiaoyue; Jin, Shijiu

2015-01-01

This paper proposes a time-space domain correlation-based method for gas leakage detection and location. It acquires the propagated signal on the skin of the plate by using a piezoelectric acoustic emission (AE) sensor array. The signal generated from the gas leakage hole (which diameter is less than 2 mm) is time continuous. By collecting and analyzing signals from different sensors’ positions in the array, the correlation among those signals in the time-space domain can be achieved. Then, the directional relationship between the sensor array and the leakage source can be calculated. The method successfully solves the real-time orientation problem of continuous ultrasonic signals generated from leakage sources (the orientation time is about 15 s once), and acquires high accuracy location information of leakage sources by the combination of multiple sets of orientation results. According to the experimental results, the mean value of the location absolute error is 5.83 mm on a one square meter plate, and the maximum location error is generally within a ±10 mm interval. Meanwhile, the error variance is less than 20.17. PMID:25860070

A new method of using sensor arrays for gas leakage location based on correlation of the time-space domain of continuous ultrasound.

PubMed

Bian, Xu; Zhang, Yu; Li, Yibo; Gong, Xiaoyue; Jin, Shijiu

2015-04-09

This paper proposes a time-space domain correlation-based method for gas leakage detection and location. It acquires the propagated signal on the skin of the plate by using a piezoelectric acoustic emission (AE) sensor array. The signal generated from the gas leakage hole (which diameter is less than 2 mm) is time continuous. By collecting and analyzing signals from different sensors' positions in the array, the correlation among those signals in the time-space domain can be achieved. Then, the directional relationship between the sensor array and the leakage source can be calculated. The method successfully solves the real-time orientation problem of continuous ultrasonic signals generated from leakage sources (the orientation time is about 15 s once), and acquires high accuracy location information of leakage sources by the combination of multiple sets of orientation results. According to the experimental results, the mean value of the location absolute error is 5.83 mm on a one square meter plate, and the maximum location error is generally within a ±10 mm interval. Meanwhile, the error variance is less than 20.17.

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Mitigating Errors in External Respiratory Surrogate-Based Models of Tumor Position

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malinowski, Kathleen T.; Fischell Department of Bioengineering, University of Maryland, College Park, MD; McAvoy, Thomas J.

2012-04-01

Purpose: To investigate the effect of tumor site, measurement precision, tumor-surrogate correlation, training data selection, model design, and interpatient and interfraction variations on the accuracy of external marker-based models of tumor position. Methods and Materials: Cyberknife Synchrony system log files comprising synchronously acquired positions of external markers and the tumor from 167 treatment fractions were analyzed. The accuracy of Synchrony, ordinary-least-squares regression, and partial-least-squares regression models for predicting the tumor position from the external markers was evaluated. The quantity and timing of the data used to build the predictive model were varied. The effects of tumor-surrogate correlation and the precisionmore » in both the tumor and the external surrogate position measurements were explored by adding noise to the data. Results: The tumor position prediction errors increased during the duration of a fraction. Increasing the training data quantities did not always lead to more accurate models. Adding uncorrelated noise to the external marker-based inputs degraded the tumor-surrogate correlation models by 16% for partial-least-squares and 57% for ordinary-least-squares. External marker and tumor position measurement errors led to tumor position prediction changes 0.3-3.6 times the magnitude of the measurement errors, varying widely with model algorithm. The tumor position prediction errors were significantly associated with the patient index but not with the fraction index or tumor site. Partial-least-squares was as accurate as Synchrony and more accurate than ordinary-least-squares. Conclusions: The accuracy of surrogate-based inferential models of tumor position was affected by all the investigated factors, except for the tumor site and fraction index.« less

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks.

PubMed

Boyen, Peter; Van Dyck, Dries; Neven, Frank; van Ham, Roeland C H J; van Dijk, Aalt D J

2011-01-01

Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.

Gaze stability, dynamic balance and participation deficits in people with multiple sclerosis at fall-risk.

PubMed

Garg, Hina; Dibble, Leland E; Schubert, Michael C; Sibthorp, Jim; Foreman, K Bo; Gappmaier, Eduard

2018-05-05

Despite the common complaints of dizziness and demyelination of afferent or efferent pathways to and from the vestibular nuclei which may adversely affect the angular Vestibulo-Ocular Reflex (aVOR) and vestibulo-spinal function in persons with Multiple Sclerosis (PwMS), few studies have examined gaze and dynamic balance function in PwMS. 1) Determine the differences in gaze stability, dynamic balance and participation measures between PwMS and controls, 2) Examine the relationships between gaze stability, dynamic balance and participation. Nineteen ambulatory PwMS at fall-risk and 14 age-matched controls were recruited. Outcomes included (a) gaze stability [angular Vestibulo-Ocular Reflex (aVOR) gain (ratio of eye to head velocity); number of Compensatory Saccades (CS) per head rotation; CS latency; gaze position error; Coefficient of Variation (CV) of aVOR gain], (b) dynamic balance [Functional Gait Assessment, FGA; four square step test], and (c) participation [dizziness handicap inventory; activities-specific balance confidence scale]. Separate independent t-tests and Pearson's correlations were calculated. PwMS were age = 53 ± 11.7yrs and had 4.2 ± 3.3 falls/yr. PwMS demonstrated significant (p<0.05) impairments in gaze stability, dynamic balance and participation measures compared to controls. CV of aVOR gain and CS latency were significantly correlated with FGA. Deficits and correlations across a spectrum of disability measures highlight the relevance of gaze and dynamic balance assessment in PwMS. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Complexity in African savannas: Direct, indirect, and cascading effects of animal densities, rainfall and vegetation availability

PubMed Central

Leeuwis, Tim; Peel, Mike

2018-01-01

Savanna ecosystems are popular subjects for interaction studies. Multiple studies have been done on the impact of elephants on vegetation, the impact of grass and browse availability on animal densities or on competition between herbivore species. Previous studies showed that elephant densities are frequently negatively correlated with densities of tall trees, and that browse and grass availability are correlated with browser and grazer density respectively. Additionally, a competition effect between browse and grass availability has been reported. These relationships are usually analysed by testing direct relationships between e.g., herbivore densities and food availability, without addressing competition effects or other indirect effects. In this study, multiple interactions in a savanna system have been analysed simultaneously using Partial Least Square-Path Modelling (PLS-PM) using mammal and vegetation data from three different wildlife reserves in southern KwaZulu-Natal. The results showed that the processes that three separate models for the three areas provided the best understanding of the importance of the different interactions. These models suggest that elephants had a negative impact on trees, but also on grass availability. The impact is stronger when elephants are not able to migrate during the dry season. Browsers and grazers were correlated with browse and grass availability, but competition between browse and grass was not detected. This study shows that due to the complexity of the interactions in an ecosystem and differences in environmental factors, these interactions are best studied per area. PLS-PM can be a useful tool for estimating direct, indirect, and cascading effects of changing animal densities in conservation areas. PMID:29768481

Domain Decomposition Algorithms for First-Order System Least Squares Methods

NASA Technical Reports Server (NTRS)

Pavarino, Luca F.

1996-01-01

Least squares methods based on first-order systems have been recently proposed and analyzed for second-order elliptic equations and systems. They produce symmetric and positive definite discrete systems by using standard finite element spaces, which are not required to satisfy the inf-sup condition. In this paper, several domain decomposition algorithms for these first-order least squares methods are studied. Some representative overlapping and substructuring algorithms are considered in their additive and multiplicative variants. The theoretical and numerical results obtained show that the classical convergence bounds (on the iteration operator) for standard Galerkin discretizations are also valid for least squares methods.

Estimating EQ-5D values from the Neck Disability Index and numeric rating scales for neck and arm pain.

PubMed

Carreon, Leah Y; Bratcher, Kelly R; Das, Nandita; Nienhuis, Jacob B; Glassman, Steven D

2014-09-01

The Neck Disability Index (NDI) and numeric rating scales (0 to 10) for neck pain and arm pain are widely used cervical spine disease-specific measures. Recent studies have shown that there is a strong relationship between the SF-6D and the NDI such that using a simple linear regression allows for the estimation of an SF-6D value from the NDI alone. Due to ease of administration and scoring, the EQ-5D is increasingly being used as a measure of utility in the clinical setting. The purpose of this study is to determine if the EQ-5D values can be estimated from commonly available cervical spine disease-specific health-related quality of life measures, much like the SF-6D. The EQ-5D, NDI, neck pain score, and arm pain score were prospectively collected in 3732 patients who presented to the authors' clinic with degenerative cervical spine disorders. Correlation coefficients for paired observations from multiple time points between the NDI, neck pain and arm pain scores, and EQ-5D were determined. Regression models were built to estimate the EQ-5D values from the NDI, neck pain, and arm pain scores. The mean age of the 3732 patients was 53.3 ± 12.2 years, and 43% were male. Correlations between the EQ-5D and the NDI, neck pain score, and arm pain score were statistically significant (p < 0.0001), with correlation coefficients of -0.77, -0.62, and -0.50, respectively. The regression equation 0.98947 + (-0.00705 × NDI) + (-0.00875 × arm pain score) + (-0.00877 × neck pain score) to predict EQ-5D had an R-square of 0.62 and a root mean square error (RMSE) of 0.146. The model using NDI alone had an R-square of 0.59 and a RMSE of 0.150. The model using the individual NDI items had an R-square of 0.46 and an RMSE of 0.172. The correlation coefficient between the observed and estimated EQ-5D scores was 0.79. There was no statistically significant difference between the actual EQ-5D score (0.603 ± 0.235) and the estimated EQ-5D score (0.603 ± 0.185) using the NDI, neck pain score, and arm pain score regression model. However, rounding off the coefficients to fewer than 5 decimal places produced less accurate results. The regression model estimating the EQ-5D from the NDI, neck pain score, and arm pain score accounted for 60% of the variability of the EQ-5D with a relatively large RMSE. This regression model may not be sufficient to accurately or reliably estimate actual EQ-5D values.

Investigation of adaptive filtering and MDL mitigation based on space-time block-coding for spatial division multiplexed coherent receivers

NASA Astrophysics Data System (ADS)

Weng, Yi; He, Xuan; Yao, Wang; Pacheco, Michelle C.; Wang, Junyi; Pan, Zhongqi

2017-07-01

In this paper, we explored the performance of space-time block-coding (STBC) assisted multiple-input multiple-output (MIMO) scheme for modal dispersion and mode-dependent loss (MDL) mitigation in spatial-division multiplexed optical communication systems, whereas the weight matrices of frequency-domain equalization (FDE) were updated heuristically using decision-directed recursive least squares (RLS) algorithm for convergence and channel estimation. The proposed STBC-RLS algorithm can achieve 43.6% enhancement on convergence rate over conventional least mean squares (LMS) for quadrature phase-shift keying (QPSK) signals with merely 16.2% increase in hardware complexity. The overall optical signal to noise ratio (OSNR) tolerance can be improved via STBC by approximately 3.1, 4.9, 7.8 dB for QPSK, 16-quadrature amplitude modulation (QAM) and 64-QAM with respective bit-error-rates (BER) and minimum-mean-square-error (MMSE).

Experimental investigation of heat transfer and fluid flow behaviour in multiple square perforated twisted tape with square wing inserts heat exchanger tube

NASA Astrophysics Data System (ADS)

Suri, Amar Raj Singh; Kumar, Anil; Maithani, Rajesh

2018-01-01

The present work deals with experimental investigation of heat transfer and fluid flow characteristics of multiple square perforated twisted tape with wing inserts in a heat exchanger tube. The range of selected geometrical parameters are, perforation width ratio (a/WT) of 0.083-0.333, twist ratio (TL/WT) of 2.0-3.5, wing depth ratio (Wd/WT) of 0.042-0.167 and number of twisted tapes (TP) of 4. The Reynolds number (Ren) selected for experimentation ranges from 5000 to 27,000. The maximum heat transfer and friction factor enhancement was found to be 6.96 and 8.34 times that of plane tube, respectively. The maximum heat transfer enhancement is observed at a a/WT of 0.250, TL/WT of 2.5, and Wd/WT of 0.167.

Experimental investigation of heat transfer and fluid flow behaviour in multiple square perforated twisted tape with square wing inserts heat exchanger tube

NASA Astrophysics Data System (ADS)

Suri, Amar Raj Singh; Kumar, Anil; Maithani, Rajesh

2018-06-01

The present work deals with experimental investigation of heat transfer and fluid flow characteristics of multiple square perforated twisted tape with wing inserts in a heat exchanger tube. The range of selected geometrical parameters are, perforation width ratio (a/WT) of 0.083-0.333, twist ratio (TL/WT) of 2.0-3.5, wing depth ratio (Wd/WT) of 0.042-0.167 and number of twisted tapes (TP) of 4. The Reynolds number (Ren) selected for experimentation ranges from 5000 to 27,000. The maximum heat transfer and friction factor enhancement was found to be 6.96 and 8.34 times that of plane tube, respectively. The maximum heat transfer enhancement is observed at a a/WT of 0.250, TL/WT of 2.5, and Wd/WT of 0.167.

Multivariable frequency domain identification via 2-norm minimization

NASA Technical Reports Server (NTRS)

Bayard, David S.

1992-01-01

The author develops a computational approach to multivariable frequency domain identification, based on 2-norm minimization. In particular, a Gauss-Newton (GN) iteration is developed to minimize the 2-norm of the error between frequency domain data and a matrix fraction transfer function estimate. To improve the global performance of the optimization algorithm, the GN iteration is initialized using the solution to a particular sequentially reweighted least squares problem, denoted as the SK iteration. The least squares problems which arise from both the SK and GN iterations are shown to involve sparse matrices with identical block structure. A sparse matrix QR factorization method is developed to exploit the special block structure, and to efficiently compute the least squares solution. A numerical example involving the identification of a multiple-input multiple-output (MIMO) plant having 286 unknown parameters is given to illustrate the effectiveness of the algorithm.

Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

Estimating EQ-5D values from the Oswestry Disability Index and numeric rating scales for back and leg pain.

PubMed

Carreon, Leah Y; Bratcher, Kelly R; Das, Nandita; Nienhuis, Jacob B; Glassman, Steven D

2014-04-15

Cross-sectional cohort. The purpose of this study is to determine whether the EuroQOL-5D (EQ-5D) can be derived from commonly available low back disease-specific health-related quality of life measures. The Oswestry Disability Index (ODI) and numeric rating scales (0-10) for back pain (BP) and leg pain (LP) are widely used disease-specific measures in patients with lumbar degenerative disorders. Increasingly, the EQ-5D is being used as a measure of utility due to ease of administration and scoring. The EQ-5D, ODI, BP, and LP were prospectively collected in 14,544 patients seen in clinic for lumbar degenerative disorders. Pearson correlation coefficients for paired observations from multiple time points between ODI, BP, LP, and EQ-5D were determined. Regression modeling was done to compute the EQ-5D score from the ODI, BP, and LP. The mean age was 53.3 ± 16.4 years and 41% were male. Correlations between the EQ-5D and the ODI, BP, and LP were statistically significant (P < 0.0001) with correlation coefficients of -0.77, -0.50, and -0.57, respectively. The regression equation: [0.97711 + (-0.00687 × ODI) + (-0.01488 × LP) + (-0.01008 × BP)] to predict EQ-5D, had an R2 of 0.61 and a root mean square error of 0.149. The model using ODI alone had an R2 of 0.57 and a root mean square error of 0.156. The model using the individual ODI items had an R2 of 0.64 and a root mean square error of 0.143. The correlation coefficient between the observed and estimated EQ-5D score was 0.78. There was no statistically significant difference between the actual EQ-5D (0.553 ± 0.238) and the estimated EQ-5D score (0.553 ± 0.186) using the ODI, BP, and LP regression model. However, rounding off the coefficients to less than 5 decimal places produced less accurate results. Unlike previous studies showing a robust relationship between low back-specific measures and the Short Form-6D, a similar relationship was not seen between the ODI, BP, LP, and the EQ-5D. Thus, the EQ-5D cannot be accurately estimated from the ODI, BP, and LP. 2.

Understanding Scaling Relations in Fracture and Mechanical Deformation of Single Crystal and Polycrystalline Silicon by Performing Atomistic Simulations at Mesoscale

DTIC Science & Technology

2009-07-16

0.25 0.26 -0.85 1 SSR SSE R SSTO SSTO = = − 2 2 ˆ( ) : Regression sum of square, ˆwhere : mean value, : value from the fitted line ˆ...Error sum of square : Total sum of square i i i i SSR Y Y Y Y SSE Y Y SSTO SSE SSR = − = − = + ∑ ∑ Statistical analysis: Coefficient of correlation

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bessac, Julie; Constantinescu, Emil; Anitescu, Mihai

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, themore » samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.« less

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

DOE PAGES

Bessac, Julie; Constantinescu, Emil; Anitescu, Mihai

2018-03-01

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, themore » samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.« less

In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors.

PubMed

Whelan, Jessica; Craven, Stephen; Glennon, Brian

2012-01-01

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed-batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off-line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Squared eigenvalue condition numbers and eigenvector correlations from the single ring theorem

NASA Astrophysics Data System (ADS)

Belinschi, Serban; Nowak, Maciej A.; Speicher, Roland; Tarnowski, Wojciech

2017-03-01

We extend the so-called ‘single ring theorem’ (Feinberg and Zee 1997 Nucl. Phys. B 504 579), also known as the Haagerup-Larsen theorem (Haagerup and Larsen 2000 J. Funct. Anal. 176 331). We do this by showing that in the limit when the size of the matrix goes to infinity a particular correlator between left and right eigenvectors of the relevant non-hermitian matrix X, being the spectral density weighted by the squared eigenvalue condition number, is given by a simple formula involving only the radial spectral cumulative distribution function of X. We show that this object allows the calculation of the conditional expectation of the squared eigenvalue condition number. We give examples and provide a cross-check of the analytic prediction by the large scale numerics.

Comparability of item quality indices from sparse data matrices with random and non-random missing data patterns.

PubMed

Wolfe, Edward W; McGill, Michael T

2011-01-01

This article summarizes a simulation study of the performance of five item quality indicators (the weighted and unweighted versions of the mean square and standardized mean square fit indices and the point-measure correlation) under conditions of relatively high and low amounts of missing data under both random and conditional patterns of missing data for testing contexts such as those encountered in operational administrations of a computerized adaptive certification or licensure examination. The results suggest that weighted fit indices, particularly the standardized mean square index, and the point-measure correlation provide the most consistent information between random and conditional missing data patterns and that these indices perform more comparably for items near the passing score than for items with extreme difficulty values.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Application of Partial Least Square (PLS) Analysis on Fluorescence Data of 8-Anilinonaphthalene-1-Sulfonic Acid, a Polarity Dye, for Monitoring Water Adulteration in Ethanol Fuel.

PubMed

Kumar, Keshav; Mishra, Ashok Kumar

2015-07-01

Fluorescence characteristic of 8-anilinonaphthalene-1-sulfonic acid (ANS) in ethanol-water mixture in combination with partial least square (PLS) analysis was used to propose a simple and sensitive analytical procedure for monitoring the adulteration of ethanol by water. The proposed analytical procedure was found to be capable of detecting even small adulteration level of ethanol by water. The robustness of the procedure is evident from the statistical parameters such as square of correlation coefficient (R(2)), root mean square of calibration (RMSEC) and root mean square of prediction (RMSEP) that were found to be well with in the acceptable limits.

Self-avoiding walk on a square lattice with correlated vacancies

NASA Astrophysics Data System (ADS)

Cheraghalizadeh, J.; Najafi, M. N.; Mohammadzadeh, H.; Saber, A.

2018-04-01

The self-avoiding walk on the square site-diluted correlated percolation lattice is considered. The Ising model is employed to realize the spatial correlations of the metric space. As a well-accepted result, the (generalized) Flory's mean-field relation is tested to measure the effect of correlation. After exploring a perturbative Fokker-Planck-like equation, we apply an enriched Rosenbluth Monte Carlo method to study the problem. To be more precise, the winding angle analysis is also performed from which the diffusivity parameter of Schramm-Loewner evolution theory (κ ) is extracted. We find that at the critical Ising (host) system, the exponents are in agreement with Flory's approximation. For the off-critical Ising system, we find also a behavior for the fractal dimension of the walker trace in terms of the correlation length of the Ising system ξ (T ) , i.e., DFSAW(T ) -DFSAW(Tc) ˜1/√{ξ (T ) } .

MRI-Based Intelligence Quotient (IQ) Estimation with Sparse Learning

PubMed Central

Wang, Liye; Wee, Chong-Yaw; Suk, Heung-Il; Tang, Xiaoying; Shen, Dinggang

2015-01-01

In this paper, we propose a novel framework for IQ estimation using Magnetic Resonance Imaging (MRI) data. In particular, we devise a new feature selection method based on an extended dirty model for jointly considering both element-wise sparsity and group-wise sparsity. Meanwhile, due to the absence of large dataset with consistent scanning protocols for the IQ estimation, we integrate multiple datasets scanned from different sites with different scanning parameters and protocols. In this way, there is large variability in these different datasets. To address this issue, we design a two-step procedure for 1) first identifying the possible scanning site for each testing subject and 2) then estimating the testing subject’s IQ by using a specific estimator designed for that scanning site. We perform two experiments to test the performance of our method by using the MRI data collected from 164 typically developing children between 6 and 15 years old. In the first experiment, we use a multi-kernel Support Vector Regression (SVR) for estimating IQ values, and obtain an average correlation coefficient of 0.718 and also an average root mean square error of 8.695 between the true IQs and the estimated ones. In the second experiment, we use a single-kernel SVR for IQ estimation, and achieve an average correlation coefficient of 0.684 and an average root mean square error of 9.166. All these results show the effectiveness of using imaging data for IQ prediction, which is rarely done in the field according to our knowledge. PMID:25822851

New Software for Market Segmentation Analysis: A Chi-Square Interaction Detector. AIR 1983 Annual Forum Paper.

ERIC Educational Resources Information Center

Lay, Robert S.

The advantages and disadvantages of new software for market segmentation analysis are discussed, and the application of this new, chi-square based procedure (CHAID), is illustrated. A comparison is presented of an earlier, binary segmentation technique (THAID) and a multiple discriminant analysis. It is suggested that CHAID is superior to earlier…

Photogrammetric Method and Software for Stream Planform Identification

NASA Astrophysics Data System (ADS)

Stonedahl, S. H.; Stonedahl, F.; Lohberg, M. M.; Lusk, K.; Miller, D.

2013-12-01

Accurately characterizing the planform of a stream is important for many purposes, including recording measurement and sampling locations, monitoring change due to erosion or volumetric discharge, and spatial modeling of stream processes. While expensive surveying equipment or high resolution aerial photography can be used to obtain planform data, our research focused on developing a close-range photogrammetric method (and accompanying free/open-source software) to serve as a cost-effective alternative. This method involves securing and floating a wooden square frame on the stream surface at several locations, taking photographs from numerous angles at each location, and then post-processing and merging data from these photos using the corners of the square for reference points, unit scale, and perspective correction. For our test field site we chose a ~35m reach along Black Hawk Creek in Sunderbruch Park (Davenport, IA), a small, slow-moving stream with overhanging trees. To quantify error we measured 88 distances between 30 marked control points along the reach. We calculated error by comparing these 'ground truth' distances to the corresponding distances extracted from our photogrammetric method. We placed the square at three locations along our reach and photographed it from multiple angles. The square corners, visible control points, and visible stream outline were hand-marked in these photos using the GIMP (open-source image editor). We wrote an open-source GUI in Java (hosted on GitHub), which allows the user to load marked-up photos, designate square corners and label control points. The GUI also extracts the marked pixel coordinates from the images. We also wrote several scripts (currently in MATLAB) that correct the pixel coordinates for radial distortion using Brown's lens distortion model, correct for perspective by forcing the four square corner pixels to form a parallelogram in 3-space, and rotate the points in order to correctly orient all photos of the same square location. Planform data from multiple photos (and multiple square locations) are combined using weighting functions that mitigate the error stemming from the markup-process, imperfect camera calibration, etc. We have used our (beta) software to mark and process over 100 photos, yielding an average error of only 1.5% relative to our 88 measured lengths. Next we plan to translate the MATLAB scripts into Python and release their source code, at which point only free software, consumer-grade digital cameras, and inexpensive building materials will be needed for others to replicate this method at new field sites. Three sample photographs of the square with the created planform and control points

Identification of quality markers of Yuanhu Zhitong tablets based on integrative pharmacology and data mining.

PubMed

Li, Ke; Li, Junfang; Su, Jin; Xiao, Xuefeng; Peng, Xiujuan; Liu, Feng; Li, Defeng; Zhang, Yi; Chong, Tao; Xu, Haiyu; Liu, Changxiao; Yang, Hongjun

2018-03-07

The quality evaluation of traditional Chinese medicine (TCM) formulations is needed to guarantee the safety and efficacy. In our laboratory, we established interaction rules between chemical quality control and biological activity evaluations to study Yuanhu Zhitong tablets (YZTs). Moreover, a quality marker (Q-marker) has recently been proposed as a new concept in the quality control of TCM. However, no appropriate methods are available for the identification of Q-markers from the complex TCM systems. We aimed to use an integrative pharmacological (IP) approach to further identify Q-markers from YZTs through the integration of multidisciplinary knowledge. In addition, data mining was used to determine the correlation between multiple constituents of this TCM and its bioactivity to improve quality control. The IP approach was used to identify the active constituents of YZTs and elucidate the molecular mechanisms by integrating chemical and biosynthetic analyses, drug metabolism, and network pharmacology. Data mining methods including grey relational analysis (GRA) and least squares support vector machine (LS-SVM) regression techniques, were used to establish the correlations among the constituents and efficacy, and dose efficacy in multiple dimensions. Seven constituents (tetrahydropalmatine, α-allocryptopine, protopine, corydaline, imperatorin, isoimperatorin, and byakangelicin) were identified as Q-markers of YZT using IP based on their high abundance, specific presence in the individual herbal constituents and the product, appropriate drug-like properties, and critical contribution to the bioactivity of the mixture of YZT constituents. Moreover, three Q-markers (protopine, α-allocryptopine, and corydaline) were highly correlated with the multiple bioactivities of the YZTs, as found using data mining. Finally, three constituents (tetrahydropalmatine, corydaline, and imperatorin) were chosen as minimum combinations that both distinguished the authentic components from false products and indicated the intensity of bioactivity to improve the quality control of YZTs. Tetrahydropalmatine, imperatorin, and corydaline could be used as minimum combinations to effectively control the quality of YZTs. Copyright © 2018. Published by Elsevier GmbH.

Changes and Correlates in Multiple Sexual Partnerships among Chinese Adult Women——Population Based Surveys in 2000 and 2006

PubMed Central

Yingying, Huang; Smith, Kumi; Suiming, Pan

2011-01-01

The sexual transmission of HIV and STI is becoming a major public health concern in China. However, studies on sexuality in China remain scant, particularly those that analyze female sexuality. This study is to investigate the prevalence of multiple sexual partnerships among adult women, and to examine trends and correlates for having more than one lifetime sexual partner. Multiple sexual partnership (MSP), coded as having one or none vs. two or more lifetime sexual partners, was the key binary outcome measure. The data were from two national probability surveys on sexual behaviors in China carried out in 2000 and 2006. The sample size of adult women was 1899 in 2000 (total sample n= 3812), and 2626 in 2006 (n=5404). Overall prevalence of MSP increased from 8.1% in 2000 to 29.6% in 2006 (Chi-square test, sig.=0.000). The most rapid changes took place among women with less education, those who worked in blue collar jobs and lower social status positions, and those living in rural areas or small towns. Women who were better educated, lived in big cities, and held management level occupations exhibited less change but had a higher baselines prevalence of MSP, suggesting that changes in MSP behavior may occur initially among women of higher socioeconomic status. Based on the 2006 dataset, significant positive correlates of MSP included more years of education, being in a long-term relationship, being middle aged, having a lower status job, going out dancing at entertainments venues, and being a state of overall health in the past 12 months. The significant recent increase in MSP among women reinforces the need to examine China’s sexual revolution in the context of a rapidly transitioning society. Findings regarding female sexuality also raise new questions to be explored in further sexuality studies, in order to better understand population sexual behaviors and to inform future HIV prevention efforts. PMID:21660755

A class of least-squares filtering and identification algorithms with systolic array architectures

NASA Technical Reports Server (NTRS)

Kalson, Seth Z.; Yao, Kung

1991-01-01

A unified approach is presented for deriving a large class of new and previously known time- and order-recursive least-squares algorithms with systolic array architectures, suitable for high-throughput-rate and VLSI implementations of space-time filtering and system identification problems. The geometrical derivation given is unique in that no assumption is made concerning the rank of the sample data correlation matrix. This method utilizes and extends the concept of oblique projections, as used previously in the derivations of the least-squares lattice algorithms. Exponentially weighted least-squares criteria are considered for both sliding and growing memory.

New Bounds on the Total-Squared-Correlation of Quaternary Signature Sets and Optimal Designs

DTIC Science & Technology

2010-03-01

2004. [8] G. S. Rajappan and M. L. Honig, “Signature sequence adaptation for DS - CDMA with multipath,” IEEE Journal on Selected Areas in Commun., vol...vol. 51, pp. 1900-1907, May 2005. [10] G. N. Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA ...Pados bounds on DS - CDMA binary signature sets,” Des., Codes Cryp- togr., vol. 30, pp. 73-84, Aug. 2003. [12] V. P. Ipatov, “On the Karystinos-Pados bounds

Simultaneous adaptation to size, distance, and curvature underwater.

PubMed

Vernoy, M W

1989-02-01

Perceptual adaptation to underwater size, distance, and curvature distortion was measured for four different adaptation conditions. These conditions consisted of (a) playing Chinese checkers underwater, (b) swimming with eyes open underwater, (c) viewing a square underwater, and (d) an air control. Significant adaptation to underwater distortions was recorded in all except the air control condition. In the viewing square condition a positive correlation between size and distance adaptation was noted. It was suggested that adaptation to curvature may have mediated the positive correlation. Possible applications for the training of divers are discussed.

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

PubMed

Lock, Eric F; Hoadley, Katherine A; Marron, J S; Nobel, Andrew B

2013-03-01

Research in several fields now requires the analysis of datasets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such datasets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data, and provides new directions for the visual exploration of joint and individual structure. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types.

Process for obtaining multiple sheet resistances for thin film hybrid microcircuit resistors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norwood, D.P.

1989-01-31

A standard thin film circuit containing Ta/sub 2/N (100 ohms/square) resistors is fabricated by depositing on a dielectric substrate successive layers of Ta/sub 2/N, Ti and Pd, with a gold layer to provide conductors. The addition of a few simple photoprocessing steps to the standard TFN manufacturing process enables the formation of Ta/sub 2/N + Ti (10 ohms/square) and Ta/sub 2/N + Ti + Pd (1 ohm/square) resistors in the same otherwise standard thin film circuit structure.

Process for obtaining multiple sheet resistances for thin film hybrid microcircuit resistors

DOEpatents

Norwood, David P.

1989-01-01

A standard thin film circuit containing Ta.sub.2 N (100 ohms/square) resirs is fabricated by depositing on a dielectric substrate successive layers of Ta.sub.2 N, Ti and Pd, with a gold layer to provide conductors. The addition of a few simple photoprocessing steps to the standeard TFN manufacturing process enables the formation of Ta.sub.2 N+Ti (10 ohms/square) and Ta.sub.2 N+Ti+Pd (1 ohm/square) resistors in the same otherwise standard thin film circuit structure.

The Quételet index revisited in children and adults.

PubMed

Chiquete, Erwin; Ruiz-Sandoval, José L; Ochoa-Guzmán, Ana; Sánchez-Orozco, Laura V; Lara-Zaragoza, Erika B; Basaldúa, Nancy; Ruiz-Madrigal, Bertha; Martínez-López, Erika; Román, Sonia; Godínez-Gutiérrez, Sergio A; Panduro, Arturo

2014-02-01

The body mass index (BMI) is based on the original concept that body weight increases as a function of height squared. As an indicator of obesity the modern BMI assumption postulates that adiposity also increases as a function of height in states of positive energy balance. To evaluate the BMI concept across different adiposity magnitudes, in both children and adults. We studied 975 individuals who underwent anthropometric evaluation: 474 children and 501 adults. Tetrapolar bioimpedance analysis was used to assess body fat and lean mass. BMI significantly correlated with percentage of body fat (%BF; children: r=0.893; adults: r=0.878) and with total fat mass (children: r=0.967; adults: r=0.953). In children, body weight, fat mass, %BF and waist circumference progressively increased as a function of height squared. In adults body weight increased as a function of height squared, but %BF actually decreased with increasing height both in men (r=-0.406; p<0.001) and women (r=-0.413; p<0.001). Most of the BMI variance in adults was explained by a positive correlation of total lean mass with height squared (r(2)=0.709), and by a negative correlation of BMI with total fat mass (r=-0.193). Body weight increases as a function of height squared. However, adiposity progressively increases as a function of height only in children. BMI is not an ideal indicator of obesity in adults since it is significantly influenced by the lean mass, even in obese individuals. Copyright © 2013 SEEN. Published by Elsevier Espana. All rights reserved.

Metameric MIMO-OOK transmission scheme using multiple RGB LEDs.

PubMed

Bui, Thai-Chien; Cusani, Roberto; Scarano, Gaetano; Biagi, Mauro

2018-05-28

In this work, we propose a novel visible light communication (VLC) scheme utilizing multiple different red green and blue triplets each with a different emission spectrum of red, green and blue for mitigating the effect of interference due to different colors using spatial multiplexing. On-off keying modulation is considered and its effect on light emission in terms of flickering, dimming and color rendering is discussed so as to demonstrate how metameric properties have been considered. At the receiver, multiple photodiodes with color filter-tuned on each transmit light emitting diode (LED) are employed. Three different detection mechanisms of color zero forcing, minimum mean square error estimation and minimum mean square error equalization are then proposed. The system performance of the proposed scheme is evaluated both with computer simulations and tests with an Arduino board implementation.

POOLMS: A computer program for fitting and model selection for two level factorial replication-free experiments

NASA Technical Reports Server (NTRS)

Amling, G. E.; Holms, A. G.

1973-01-01

A computer program is described that performs a statistical multiple-decision procedure called chain pooling. It uses a number of mean squares assigned to error variance that is conditioned on the relative magnitudes of the mean squares. The model selection is done according to user-specified levels of type 1 or type 2 error probabilities.

Penrose high-dynamic-range imaging

NASA Astrophysics Data System (ADS)

Li, Jia; Bai, Chenyan; Lin, Zhouchen; Yu, Jian

2016-05-01

High-dynamic-range (HDR) imaging is becoming increasingly popular and widespread. The most common multishot HDR approach, based on multiple low-dynamic-range images captured with different exposures, has difficulties in handling camera and object movements. The spatially varying exposures (SVE) technology provides a solution to overcome this limitation by obtaining multiple exposures of the scene in only one shot but suffers from a loss in spatial resolution of the captured image. While aperiodic assignment of exposures has been shown to be advantageous during reconstruction in alleviating resolution loss, almost all the existing imaging sensors use the square pixel layout, which is a periodic tiling of square pixels. We propose the Penrose pixel layout, using pixels in aperiodic rhombus Penrose tiling, for HDR imaging. With the SVE technology, Penrose pixel layout has both exposure and pixel aperiodicities. To investigate its performance, we have to reconstruct HDR images in square pixel layout from Penrose raw images with SVE. Since the two pixel layouts are different, the traditional HDR reconstruction methods are not applicable. We develop a reconstruction method for Penrose pixel layout using a Gaussian mixture model for regularization. Both quantitative and qualitative results show the superiority of Penrose pixel layout over square pixel layout.

Multiple sclerosis and employment: Associations of psychological factors and work instability.

PubMed

Wicks, Charlotte Rose; Ward, Karl; Stroud, Amanda; Tennant, Alan; Ford, Helen L

2016-10-12

People with multiple sclerosis often stop working earlier than expected. Psychological factors may have an impact on job retention. Investigation may inform interventions to help people stay in work. To investigate the associations between psychological factors and work instability in people with multiple sclerosis. A multi-method, 2-phased study. Focus groups were held to identify key themes. Questionnaire packs using validated scales of the key themes were completed at baseline and at 8-month follow-up. Four key psychological themes emerged. Out of 208 study subjects 57.2% reported medium/high risk of job loss, with marginal changes at 8 months. Some psychological variables fluctuated significantly, e.g. depression fell from 24.6% to 14.5%. Work instability and anxiety and depression were strongly correlated (χ2 p < 0.001). Those with probable depression at baseline had 7.1 times increased odds of medium/high work instability, and baseline depression levels also predicted later work instability (Hosmer-Lemeshow test 0.899; Nagelkerke R Square 0.579). Psychological factors fluctuated over the 8-month follow-up period. Some psychological variables, including anxiety and depression, were significantly associated with, and predictive of, work instability. Longitudinal analysis should further identify how these psychological attributes impact on work instability and potential job loss in the longer term.

Kinetics and dynamics of the C(3P) + H2O reaction on a full-dimensional accurate triplet state potential energy surface.

PubMed

Li, Jun; Xie, Changjian; Guo, Hua

2017-08-30

A full dimensional accurate potential energy surface (PES) for the C( 3 P) and H 2 O reaction is developed based on ∼34 000 data points calculated at the level of the explicitly correlated unrestricted coupled cluster method with single, double, and perturbative triple excitations with the augmented correlation-consistent polarized triple zeta basis set (CCSD(T)-F12a/AVTZ). The PES is invariant with respect to the permutation of the two hydrogen atoms and the total root mean square error (RMSE) of the fit is only 0.31 kcal mol -1 . The PES features two barriers in the entrance channel and several potential minima, as well as multiple product channels. The rate coefficients of this reaction calculated using a transition-state theory and quasi-classical trajectory (QCT) method are small near room temperature, consistent with experiments. The reaction dynamics is also investigated with QCT on the new PES, which found that the reactivity is constrained by the entrance barriers and the final product branching is not statistical.

Active dynamics of colloidal particles in time-varying laser speckle patterns

PubMed Central

Bianchi, Silvio; Pruner, Riccardo; Vizsnyiczai, Gaszton; Maggi, Claudio; Di Leonardo, Roberto

2016-01-01

Colloidal particles immersed in a dynamic speckle pattern experience an optical force that fluctuates both in space and time. The resulting dynamics presents many interesting analogies with a broad class of non-equilibrium systems like: active colloids, self propelled microorganisms, transport in dynamical intracellular environments. Here we show that the use of a spatial light modulator allows to generate light fields that fluctuate with controllable space and time correlations and a prescribed average intensity profile. In particular we generate ring-shaped random patterns that can confine a colloidal particle over a quasi one-dimensional random energy landscape. We find a mean square displacement that is diffusive at both short and long times, while a superdiffusive or subdiffusive behavior is observed at intermediate times depending on the value of the speckles correlation time. We propose two alternative models for the mean square displacement in the two limiting cases of a short or long speckles correlation time. A simple interpolation formula is shown to account for the full phenomenology observed in the mean square displacement across the entire range from fast to slow fluctuating speckles. PMID:27279540

Variable criteria sequential stopping rule: Validity and power with repeated measures ANOVA, multiple correlation, MANOVA and relation to Chi-square distribution.

PubMed

Fitts, Douglas A

2017-09-21

The variable criteria sequential stopping rule (vcSSR) is an efficient way to add sample size to planned ANOVA tests while holding the observed rate of Type I errors, α o , constant. The only difference from regular null hypothesis testing is that criteria for stopping the experiment are obtained from a table based on the desired power, rate of Type I errors, and beginning sample size. The vcSSR was developed using between-subjects ANOVAs, but it should work with p values from any type of F test. In the present study, the α o remained constant at the nominal level when using the previously published table of criteria with repeated measures designs with various numbers of treatments per subject, Type I error rates, values of ρ, and four different sample size models. New power curves allow researchers to select the optimal sample size model for a repeated measures experiment. The criteria held α o constant either when used with a multiple correlation that varied the sample size model and the number of predictor variables, or when used with MANOVA with multiple groups and two levels of a within-subject variable at various levels of ρ. Although not recommended for use with χ 2 tests such as the Friedman rank ANOVA test, the vcSSR produces predictable results based on the relation between F and χ 2 . Together, the data confirm the view that the vcSSR can be used to control Type I errors during sequential sampling with any t- or F-statistic rather than being restricted to certain ANOVA designs.

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Prediction of properties and elemental composition of biomass pyrolysis oils by NMR and partial least squares analysis

USDA-ARS?s Scientific Manuscript database

Several partial least squares (PLS) models were created correlating various properties and chemical composition measurements with the 1H and 13C NMR spectra of 73 different of pyrolysis bio-oil samples from various biomass sources (crude and intermediate products), finished oils and small molecule s...

Nondestructive evaluation of soluble solid content in strawberry by near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Wang, Xiu; Peng, Yankun

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R2 c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R2 p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R2 c = 0.9590 in the calibration set; and RMSEP = 0.2892, R2 p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

PubMed Central

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-01-01

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS. PMID:27420066

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms.

PubMed

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-07-12

Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR) observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS) pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.

Correlation of USMLE Step 1 scores with performance on dermatology in-training examinations.

PubMed

Fening, Katherine; Vander Horst, Anthony; Zirwas, Matthew

2011-01-01

Although United States Medical Licensing Examination (USMLE) Step 1 was not designed to predict resident performance, scores are used to compare residency applicants. Multiple studies have displayed a significant correlation among Step 1 scores, in-training examination (ITE) scores, and board passage, although no such studies have been performed in dermatology. The purpose of this study is to determine if this correlation exists in dermatology, and how much of the variability in ITE scores is a result of differences in Step 1 scores. This study also seeks to determine if it is appropriate to individualize expectations for resident ITE performance. This project received institutional review board exemption. From 5 dermatology residency programs (86 residents), we collected Step 1 and ITE scores for each of the 3 years of dermatology residency, and recorded passage/failure on boards. Bivariate Pearson correlation analysis was used to assess correlation between USMLE and ITE scores. Ordinary least squares regression was computed to determine how much USMLE scores contribute to ITE variability. USMLE and ITE score correlations were highly significant (P < .001). Correlation coefficients with USMLE were: 0.467, 0.541, and 0.527 for ITE in years 1, 2, and 3, respectively. Variability in ITE scores caused by differences in USMLE scores were: ITE first-year residency = 21.8%, ITE second-year residency = 29.3%, and ITE third-year residency = 27.8%. This study had a relatively small sample size, with data from only 5 programs. There is a moderate correlation between USMLE and ITE scores, with USMLE scores explaining ∼26% of the variability in ITE scores. Copyright © 2009 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Do MCAT scores predict USMLE scores? An analysis on 5 years of medical student data.

PubMed

Gauer, Jacqueline L; Wolff, Josephine M; Jackson, J Brooks

2016-01-01

The purpose of this study was to determine the associations and predictive values of Medical College Admission Test (MCAT) component and composite scores prior to 2015 with U.S. Medical Licensure Exam (USMLE) Step 1 and Step 2 Clinical Knowledge (CK) scores, with a focus on whether students scoring low on the MCAT were particularly likely to continue to score low on the USMLE exams. Multiple linear regression, correlation, and chi-square analyses were performed to determine the relationship between MCAT component and composite scores and USMLE Step 1 and Step 2 CK scores from five graduating classes (2011-2015) at the University of Minnesota Medical School ( N =1,065). The multiple linear regression analyses were both significant ( p <0.001). The three MCAT component scores together explained 17.7% of the variance in Step 1 scores ( p< 0.001) and 12.0% of the variance in Step 2 CK scores ( p <0.001). In the chi-square analyses, significant, albeit weak associations were observed between almost all MCAT component scores and USMLE scores (Cramer's V ranged from 0.05 to 0.24). Each of the MCAT component scores was significantly associated with USMLE Step 1 and Step 2 CK scores, although the effect size was small. Being in the top or bottom scoring range of the MCAT exam was predictive of being in the top or bottom scoring range of the USMLE exams, although the strengths of the associations were weak to moderate. These results indicate that MCAT scores are predictive of student performance on the USMLE exams, but, given the small effect sizes, should be considered as part of the holistic view of the student.

Do MCAT scores predict USMLE scores? An analysis on 5 years of medical student data

PubMed Central

Gauer, Jacqueline L.; Wolff, Josephine M.; Jackson, J. Brooks

2016-01-01

Introduction The purpose of this study was to determine the associations and predictive values of Medical College Admission Test (MCAT) component and composite scores prior to 2015 with U.S. Medical Licensure Exam (USMLE) Step 1 and Step 2 Clinical Knowledge (CK) scores, with a focus on whether students scoring low on the MCAT were particularly likely to continue to score low on the USMLE exams. Method Multiple linear regression, correlation, and chi-square analyses were performed to determine the relationship between MCAT component and composite scores and USMLE Step 1 and Step 2 CK scores from five graduating classes (2011–2015) at the University of Minnesota Medical School (N=1,065). Results The multiple linear regression analyses were both significant (p<0.001). The three MCAT component scores together explained 17.7% of the variance in Step 1 scores (p<0.001) and 12.0% of the variance in Step 2 CK scores (p<0.001). In the chi-square analyses, significant, albeit weak associations were observed between almost all MCAT component scores and USMLE scores (Cramer's V ranged from 0.05 to 0.24). Discussion Each of the MCAT component scores was significantly associated with USMLE Step 1 and Step 2 CK scores, although the effect size was small. Being in the top or bottom scoring range of the MCAT exam was predictive of being in the top or bottom scoring range of the USMLE exams, although the strengths of the associations were weak to moderate. These results indicate that MCAT scores are predictive of student performance on the USMLE exams, but, given the small effect sizes, should be considered as part of the holistic view of the student. PMID:27702431

Analysis of medical litigation among patients with medical disputes in cosmetic surgery in Taiwan.

PubMed

Lyu, Shu-Yu; Liao, Chuh-Kai; Chang, Kao-Ping; Tsai, Shang-Ta; Lee, Ming-Been; Tsai, Feng-Chou

2011-10-01

This study aimed to investigate the key factors in medical disputes (arguments) among female patients after cosmetic surgery in Taiwan and to explore the correlates of medical litigation. A total of 6,888 patients (3,210 patients from two hospitals and 3,678 patients from two clinics) received cosmetic surgery from January 2001 to December 2009. The inclusion criteria specified female patients with a medical dispute. Chi-square testing and multiple logistic regression analysis were used to analyze the data. Of the 43 patients who had a medical dispute (hospitals, 0.53%; clinics, 0.73%), 9 plaintiffs eventually filed suit against their plastic surgeons. Such an outcome exhibited a decreasing annual trend. The hospitals and clinics did not differ significantly in terms of patient profiles. The Chi-square test showed that most patients with a medical dispute (p < 0.05) were older than 30 years, were divorced or married, had received operations under general anesthesia, had no economic stress, had a history of medical litigation, and eventually did not sue the surgeons. The test results also showed that the surgeon's seniority and experience significantly influenced the possibility of medical dispute and nonlitigation. Multiple logistical regression analysis further showed that the patients who did decide to enter into litigation had two main related factors: marital stress (odds ratio [OR], 10.67; 95% confidence interval [CI], 1.20-94.73) and an education level below junior college (OR, 9.33; 95% CI, 1.01-86.36). The study findings suggest that the key characteristics of patients and surgeons should be taken into consideration not only in the search for ways to enhance pre- and postoperative communication but also as useful information for expert testimony in the inquisitorial law system.

Estimating Dbh of Trees Employing Multiple Linear Regression of the best Lidar-Derived Parameter Combination Automated in Python in a Natural Broadleaf Forest in the Philippines

NASA Astrophysics Data System (ADS)

Ibanez, C. A. G.; Carcellar, B. G., III; Paringit, E. C.; Argamosa, R. J. L.; Faelga, R. A. G.; Posilero, M. A. V.; Zaragosa, G. P.; Dimayacyac, N. A.

2016-06-01

Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike's Information Criterion) and BIC (Bayesian Information Criterion) was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO) Coefficient and the Barlett's Test for Spherecity (BTS).

Exogenous attention influences visual short-term memory in infants.

PubMed

Ross-Sheehy, Shannon; Oakes, Lisa M; Luck, Steven J

2011-05-01

Two experiments examined the hypothesis that developing visual attentional mechanisms influence infants' Visual Short-Term Memory (VSTM) in the context of multiple items. Five- and 10-month-old infants (N = 76) received a change detection task in which arrays of three differently colored squares appeared and disappeared. On each trial one square changed color and one square was cued; sometimes the cued item was the changing item, and sometimes the changing item was not the cued item. Ten-month-old infants exhibited enhanced memory for the cued item when the cue was a spatial pre-cue (Experiment 1) and 5-month-old infants exhibited enhanced memory for the cued item when the cue was relative motion (Experiment 2). These results demonstrate for the first time that infants younger than 6 months can encode information in VSTM about individual items in multiple-object arrays, and that attention-directing cues influence both perceptual and VSTM encoding of stimuli in infants as in adults.

Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at square root of s = 7 TeV.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Bergauer, T; Dragicevic, M; Erö, J; Fabjan, C; Friedl, M; Frühwirth, R; Ghete, V M; Hammer, J; Hänsel, S; Hoch, M; Hörmann, N; Hrubec, J; Jeitler, M; Kasieczka, G; Kiesenhofer, W; Krammer, M; Liko, D; Mikulec, I; Pernicka, M; Rohringer, H; Schöfbeck, R; Strauss, J; Taurok, A; Teischinger, F; Waltenberger, W; Walzel, G; Widl, E; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Benucci, L; Ceard, L; De Wolf, E A; Hashemi, M; Janssen, X; Maes, T; Mucibello, L; Ochesanu, S; Roland, B; Rougny, R; Selvaggi, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Adler, V; Beauceron, S; Blyweert, S; D'Hondt, J; Devroede, O; Kalogeropoulos, A; Maes, J; Maes, M; Tavernier, S; Van Doninck, W; Van Mulders, P; Villella, I; Chabert, E C; Charaf, O; Clerbaux, B; De Lentdecker, G; Dero, V; Gay, A P R; Hammad, G H; Marage, P E; Vander Velde, C; Vanlaer, P; Wickens, J; Costantini, S; Grunewald, M; Klein, B; Marinov, A; Ryckbosch, D; Thyssen, F; Tytgat, M; Vanelderen, L; Verwilligen, P; Walsh, S; Zaganidis, N; Basegmez, S; Bruno, G; Caudron, J; De Favereau De Jeneret, J; Delaere, C; Demin, P; Favart, D; Giammanco, A; Grégoire, G; Hollar, J; Lemaitre, V; Militaru, O; Ovyn, S; Pagano, D; Pin, A; Piotrzkowski, K; Quertenmont, L; Schul, N; Beliy, N; Caebergs, T; Daubie, E; Alves, G A; Pol, M E; Souza, M H G; Carvalho, W; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Mundim, L; Oguri, V; Santoro, A; Silva Do Amaral, S M; Sznajder, A; Torres Da Silva De Araujo, F; Dias, F A; Dias, M A F; Fernandez Perez Tomei, T R; Gregores, E M; Marinho, F; Novaes, S F; Padula, Sandra S; Darmenov, N; Dimitrov, L; Genchev, V; Iaydjiev, P; Piperov, S; Stoykova, S; Sultanov, G; Trayanov, R; Vankov, I; Dyulendarova, M; Hadjiiska, R; Kozhuharov, V; Litov, L; Marinova, E; Mateev, M; Pavlov, B; Petkov, P; Bian, J G; Chen, G M; Chen, H S; Jiang, C H; Liang, D; Liang, S; Wang, J; Wang, J; Wang, X; Wang, Z; Yang, M; Zang, J; Zhang, Z; Ban, Y; Guo, S; Hu, Z; Mao, Y; Qian, S J; Teng, H; Zhu, B; Cabrera, A; Carrillo Montoya, C A; Gomez Moreno, B; Ocampo Rios, A A; Osorio Oliveros, A F; Sanabria, J C; Godinovic, N; Lelas, D; Lelas, K; Plestina, R; Polic, D; Puljak, I; Antunovic, Z; Dzelalija, M; Brigljevic, V; Duric, S; Kadija, K; Morovic, S; Attikis, A; Fereos, R; Galanti, M; Mousa, J; Nicolaou, C; Papadakis, A; Ptochos, F; Razis, P A; Rykaczewski, H; Tsiakkouri, D; Zinonos, Z; Mahmoud, M; Hektor, A; Kadastik, M; Kannike, K; Müntel, M; Raidal, M; Rebane, L; Azzolini, V; Eerola, P; Czellar, S; Härkönen, J; Heikkinen, A; Karimäki, V; Kinnunen, R; Klem, J; Kortelainen, M J; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Ungaro, D; Wendland, L; Banzuzi, K; Korpela, A; Tuuva, T; Sillou, D; Besancon, M; Dejardin, M; Denegri, D; Descamps, J; Fabbro, B; Faure, J L; Ferri, F; Ganjour, S; Gentit, F X; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Locci, E; Malcles, J; Marionneau, M; Millischer, L; Rander, J; Rosowsky, A; Rousseau, D; Titov, M; Verrecchia, P; Baffioni, S; Bianchini, L; Bluj, M; Broutin, C; Busson, P; Charlot, C; Dobrzynski, L; Elgammal, S; Granier de Cassagnac, R; Haguenauer, M; Kalinowski, A; Miné, P; Paganini, P; Sabes, D; Sirois, Y; Thiebaux, C; Zabi, A; Agram, J-L; Besson, A; Bloch, D; Bodin, D; Brom, J-M; Cardaci, M; Conte, E; Drouhin, F; Ferro, C; Fontaine, J-C; Gelé, D; Goerlach, U; Greder, S; Juillot, P; Karim, M; Le Bihan, A-C; Mikami, Y; Speck, J; Van Hove, P; Fassi, F; Mercier, D; Baty, C; Beaupere, N; Bedjidian, M; Bondu, O; Boudoul, G; Boumediene, D; Brun, H; Chanon, N; Chierici, R; Contardo, D; Depasse, P; El Mamouni, H; Fay, J; Gascon, S; Ille, B; Kurca, T; Le Grand, T; Lethuillier, M; Mirabito, L; Perries, S; Tosi, S; Tschudi, Y; Verdier, P; Xiao, H; Roinishvili, V; Anagnostou, G; Edelhoff, M; Feld, L; Heracleous, N; Hindrichs, O; Jussen, R; Klein, K; Merz, J; Mohr, N; Ostapchuk, A; Perieanu, A; Raupach, F; Sammet, J; Schael, S; Sprenger, D; Weber, H; Weber, M; Wittmer, B; Actis, O; Ata, M; Bender, W; Biallass, P; Erdmann, M; Frangenheim, J; Hebbeker, T; Hinzmann, A; Hoepfner, K; Hof, C; Kirsch, M; Klimkovich, T; Kreuzer, P; Lanske, D; Magass, C; Merschmeyer, M; Meyer, A; Papacz, P; Pieta, H; Reithler, H; Schmitz, S A; Sonnenschein, L; Sowa, M; Steggemann, J; Teyssier, D; Zeidler, C; Bontenackels, M; Davids, M; Duda, M; Flügge, G; Geenen, H; Giffels, M; Haj Ahmad, W; Heydhausen, D; Kress, T; Kuessel, Y; Linn, A; Nowack, A; Perchalla, L; Pooth, O; Sauerland, P; Stahl, A; Thomas, M; Tornier, D; Zoeller, M H; Aldaya Martin, M; Behrenhoff, W; Behrens, U; Bergholz, M; Borras, K; Campbell, A; Castro, E; Dammann, D; Eckerlin, G; Flossdorf, A; Flucke, G; Geiser, A; Hauk, J; Jung, H; Kasemann, M; Katkov, I; Kleinwort, C; Kluge, H; Knutsson, A; Kuznetsova, E; Lange, W; Lohmann, W; Mankel, R; Marienfeld, M; Melzer-Pellmann, I-A; Meyer, A B; Mnich, J; Mussgiller, A; Olzem, J; Parenti, A; Raspereza, A; Schmidt, R; Schoerner-Sadenius, T; Sen, N; Stein, M; Tomaszewska, J; Volyanskyy, D; Wissing, C; Autermann, C; Draeger, J; Eckstein, D; Enderle, H; Gebbert, U; Kaschube, K; Kaussen, G; Klanner, R; Mura, B; Naumann-Emme, S; Nowak, F; Sander, C; Schettler, H; Schleper, P; Schröder, M; Schum, T; Schwandt, J; Stadie, H; Steinbrück, G; Thomsen, J; Wolf, R; Bauer, J; Buege, V; Cakir, A; Chwalek, T; Daeuwel, D; De Boer, W; Dierlamm, A; Dirkes, G; Feindt, M; Gruschke, J; Hackstein, C; Hartmann, F; Heinrich, M; Held, H; Hoffmann, K H; Honc, S; Kuhr, T; Martschei, D; Mueller, S; Müller, Th; Niegel, M; Oberst, O; Oehler, A; Ott, J; Peiffer, T; Piparo, D; Quast, G; Rabbertz, K; Ratnikov, F; Renz, M; Sabellek, A; Saout, C; Scheurer, A; Schieferdecker, P; Schilling, F-P; Schott, G; Simonis, H J; Stober, F M; Troendle, D; Wagner-Kuhr, J; Zeise, M; Zhukov, V; Ziebarth, E B; Daskalakis, G; Geralis, T; Kyriakis, A; Loukas, D; Manolakos, I; Markou, A; Markou, C; Mavrommatis, C; Petrakou, E; Gouskos, L; Katsas, P; Panagiotou, A; Evangelou, I; Kokkas, P; Manthos, N; Papadopoulos, I; Patras, V; Triantis, F A; Aranyi, A; Bencze, G; Boldizsar, L; Debreczeni, G; Hajdu, C; Horvath, D; Kapusi, A; Krajczar, K; Laszlo, A; Sikler, F; Vesztergombi, G; Beni, N; Molnar, J; Palinkas, J; Szillasi, Z; Veszpremi, V; Raics, P; Trocsanyi, Z L; Ujvari, B; Bansal, S; Beri, S B; Bhatnagar, V; Jindal, M; Kaur, M; Kohli, J M; Mehta, M Z; Nishu, N; Saini, L K; Sharma, A; Sharma, R; Singh, A P; Singh, J B; Singh, S P; Ahuja, S; Bhattacharya, S; Chauhan, S; Choudhary, B C; Gupta, P; Jain, S; Jain, S; Kumar, A; Ranjan, K; Shivpuri, R K; Choudhury, R K; Dutta, D; Kailas, S; Kataria, S K; Mohanty, A K; Pant, L M; Shukla, P; Suggisetti, P; Aziz, T; Guchait, M; Gurtu, A; Maity, M; Majumder, D; Majumder, G; Mazumdar, K; Mohanty, G B; Saha, A; Sudhakar, K; Wickramage, N; Banerjee, S; Dugad, S; Mondal, N K; Arfaei, H; Bakhshiansohi, H; Fahim, A; Jafari, A; Mohammadi Najafabadi, M; Paktinat Mehdiabadi, S; Safarzadeh, B; Zeinali, M; Abbrescia, M; Barbone, L; Colaleo, A; Creanza, D; De Filippis, N; De Palma, M; Dimitrov, A; Fedele, F; Fiore, L; Iaselli, G; Lusito, L; Maggi, G; Maggi, M; Manna, N; Marangelli, B; My, S; Nuzzo, S; Pierro, G A; Pompili, A; Pugliese, G; Romano, F; Roselli, G; Selvaggi, G; Silvestris, L; Trentadue, R; Tupputi, S; Zito, G; Abbiendi, G; Benvenuti, A C; Bonacorsi, D; Braibant-Giacomelli, S; Castro, A; Cavallo, F R; Codispoti, G; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Giunta, M; Grandi, C; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Odorici, F; Perrotta, A; Rossi, A M; Rovelli, T; Siroli, G; Travaglini, R; Albergo, S; Cappello, G; Chiorboli, M; Costa, S; Tricomi, A; Tuve, C; Barbagli, G; Broccolo, G; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Frosali, S; Gallo, E; Genta, C; Lenzi, P; Meschini, M; Paoletti, S; Sguazzoni, G; Tropiano, A; Benussi, L; Bianco, S; Colafranceschi, S; Fabbri, F; Piccolo, D; Fabbricatore, P; Musenich, R; Benaglia, A; Cerati, G B; De Guio, F; Di Matteo, L; Ghezzi, A; Govoni, P; Malberti, M; Malvezzi, S; Martelli, A; Massironi, A; Menasce, D; Miccio, V; Moroni, L; Negri, P; Paganoni, M; Pedrini, D; Ragazzi, S; Redaelli, N; Sala, S; Salerno, R; Tabarelli de Fatis, T; Tancini, V; Taroni, S; Buontempo, S; Cimmino, A; De Cosa, A; De Gruttola, M; Fabozzi, F; Iorio, A O M; Lista, L; Noli, P; Paolucci, P; Azzi, P; Bacchetta, N; Bellan, P; Bellato, M; Biasotto, M; Bisello, D; Carlin, R; Checchia, P; De Mattia, M; Dorigo, T; Fanzago, F; Gasparini, F; Giubilato, P; Gresele, A; Lacaprara, S; Lazzizzera, I; Margoni, M; Maron, G; Meneguzzo, A T; Nespolo, M; Perrozzi, L; Pozzobon, N; Ronchese, P; Simonetto, F; Torassa, E; Tosi, M; Triossi, A; Vanini, S; Zumerle, G; Baesso, P; Berzano, U; Riccardi, C; Torre, P; Vitulo, P; Viviani, C; Biasini, M; Bilei, G M; Caponeri, B; Fanò, L; Lariccia, P; Lucaroni, A; Mantovani, G; Menichelli, M; Nappi, A; Santocchia, A; Servoli, L; Valdata, M; Volpe, R; Azzurri, P; Bagliesi, G; Bernardini, J; Boccali, T; Castaldi, R; Dagnolo, R T; Dell'Orso, R; Fiori, F; Foà, L; Giassi, A; Kraan, A; Ligabue, F; Lomtadze, T; Martini, L; Messineo, A; Palla, F; Palmonari, F; Segneri, G; Serban, A T; Spagnolo, P; Tenchini, R; Tonelli, G; Venturi, A; Verdini, P G; Barone, L; Cavallari, F; Del Re, D; Di Marco, E; Diemoz, M; Franci, D; Grassi, M; Longo, E; Organtini, G; Palma, A; Pandolfi, F; Paramatti, R; Rahatlou, S; Amapane, N; Arcidiacono, R; Argiro, S; Arneodo, M; Biino, C; Botta, C; Cartiglia, N; Castello, R; Costa, M; Demaria, N; Graziano, A; Mariotti, C; Marone, M; Maselli, S; Migliore, E; Mila, G; Monaco, V; Musich, M; Obertino, M M; Pastrone, N; Pelliccioni, M; Romero, A; Ruspa, M; Sacchi, R; Solano, A; Staiano, A; Trocino, D; Vilela Pereira, A; Ambroglini, F; Belforte, S; Cossutti, F; Della Ricca, G; Gobbo, B; Montanino, D; Penzo, A; Chang, S; Chung, J; Kim, D H; Kim, G N; Kim, J E; Kong, D J; Park, H; Son, D C; Kim, Zero; Kim, J Y; Song, S; Hong, B; Kim, H; Kim, J H; Kim, T J; Lee, K S; Moon, D H; Park, S K; Rhee, H B; Sim, K S; Choi, M; Kang, S; Kim, H; Park, C; Park, I C; Park, S; Choi, S; Choi, Y; Choi, Y K; Goh, J; Lee, J; Lee, S; Seo, H; Yu, I; Janulis, M; Martisiute, D; Petrov, P; Sabonis, T; Castilla Valdez, H; De La Cruz Burelo, E; Lopez-Fernandez, R; Sánchez Hernández, A; Villaseñor-Cendejas, L M; Carrillo Moreno, S; Salazar Ibarguen, H A; Casimiro Linares, E; Morelos Pineda, A; Reyes-Santos, M A; Allfrey, P; Krofcheck, D; Tam, J; Aumeyr, T; Butler, P H; Signal, T; Williams, J C; Ahmad, M; Ahmed, I; Asghar, M I; Hoorani, H R; Khan, W A; Khurshid, T; Qazi, S; Cwiok, M; Dominik, W; Doroba, K; Konecki, M; Krolikowski, J; Frueboes, T; Gokieli, R; Górski, M; Kazana, M; Nawrocki, K; Szleper, M; Wrochna, G; Zalewski, P; Almeida, N; David, A; Faccioli, P; Ferreira Parracho, P G; Gallinaro, M; Mini, G; Musella, P; Nayak, A; Raposo, L; Ribeiro, P Q; Seixas, J; Silva, P; Soares, D; Varela, J; Wöhri, H K; Altsybeev, I; Belotelov, I; Bunin, P; Finger, M; Finger, M; Golutvin, I; Kamenev, A; Karjavin, V; Kozlov, G; Lanev, A; Moisenz, P; Palichik, V; Perelygin, V; Shmatov, S; Smirnov, V; Volodko, A; Zarubin, A; Bondar, N; Golovtsov, V; Ivanov, Y; Kim, V; Levchenko, P; Smirnov, I; Sulimov, V; Uvarov, L; Vavilov, S; Vorobyev, A; Andreev, Yu; Gninenko, S; Golubev, N; Kirsanov, M; Krasnikov, N; Matveev, V; Pashenkov, A; Toropin, A; Troitsky, S; Epshteyn, V; Gavrilov, V; Ilina, N; Kaftanov, V; Kossov, M; Krokhotin, A; Kuleshov, S; Oulianov, A; Safronov, G; Semenov, S; Shreyber, I; Stolin, V; Vlasov, E; Zhokin, A; Boos, E; Dubinin, M; Dudko, L; Ershov, A; Gribushin, A; Kodolova, O; Lokhtin, I; Obraztsov, S; Petrushanko, S; Sarycheva, L; Savrin, V; Snigirev, A; Andreev, V; Dremin, I; Kirakosyan, M; Rusakov, S V; Vinogradov, A; Azhgirey, I; Bitioukov, S; Datsko, K; Grishin, V; Kachanov, V; Konstantinov, D; Krychkine, V; Petrov, V; Ryutin, R; Slabospitsky, S; Sobol, A; Sytine, A; Tourtchanovitch, L; Troshin, S; Tyurin, N; Uzunian, A; Volkov, A; Adzic, P; Djordjevic, M; Krpic, D; Maletic, D; Milosevic, J; Puzovic, J; Aguilar-Benitez, M; Alcaraz Maestre, J; Arce, P; Battilana, C; Calvo, E; Cepeda, M; Cerrada, M; Chamizo Llatas, M; Colino, N; De La Cruz, B; Diez Pardos, C; Fernandez Bedoya, C; Fernández Ramos, J P; Ferrando, A; Flix, J; Fouz, M C; Garcia-Abia, P; Gonzalez Lopez, O; Goy Lopez, S; Hernandez, J M; Josa, M I; Merino, G; Puerta Pelayo, J; Redondo, I; Romero, L; Santaolalla, J; Willmott, C; Albajar, C; de Trocóniz, J F; Cuevas, J; Fernandez Menendez, J; Gonzalez Caballero, I; Lloret Iglesias, L; Vizan Garcia, J M; Cabrillo, I J; Calderon, A; Chuang, S H; Diaz Merino, I; Diez Gonzalez, C; Duarte Campderros, J; Fernandez, M; Gomez, G; Gonzalez Sanchez, J; Gonzalez Suarez, R; Jorda, C; Lobelle Pardo, P; Lopez Virto, A; Marco, J; Marco, R; Martinez Rivero, C; Martinez Ruiz del Arbol, P; Matorras, F; Rodrigo, T; Ruiz Jimeno, A; Scodellaro, L; Sobron Sanudo, M; Vila, I; Vilar Cortabitarte, R; Abbaneo, D; Auffray, E; Baillon, P; Ball, A H; Barney, D; Beaudette, F; Bell, A J; Bellan, R; Benedetti, D; Bernet, C; Bialas, W; Bloch, P; Bocci, A; Bolognesi, S; Breuker, H; Brona, G; Bunkowski, K; Camporesi, T; Cano, E; Cattai, A; Cerminara, G; Christiansen, T; Coarasa Perez, J A; Covarelli, R; Curé, B; Dahms, T; De Roeck, A; Elliott-Peisert, A; Funk, W; Gaddi, A; Gennai, S; Gerwig, H; Gigi, D; Gill, K; Giordano, D; Glege, F; Gomez-Reino Garrido, R; Gowdy, S; Guiducci, L; Hansen, M; Hartl, C; Harvey, J; Hegner, B; Henderson, C; Hoffmann, H F; Honma, A; Innocente, V; Janot, P; Lecoq, P; Leonidopoulos, C; Lourenço, C; Macpherson, A; Mäki, T; Malgeri, L; Mannelli, M; Masetti, L; Mavromanolakis, G; Meijers, F; Mersi, S; Meschi, E; Moser, R; Mozer, M U; Mulders, M; Nesvold, E; Orsini, L; Perez, E; Petrilli, A; Pfeiffer, A; Pierini, M; Pimiä, M; Racz, A; Rolandi, G; Rovelli, C; Rovere, M; Ryjov, V; Sakulin, H; Schäfer, C; Schwick, C; Segoni, I; Sharma, A; Siegrist, P; Simon, M; Sphicas, P; Spiga, D; Spiropulu, M; Stöckli, F; Traczyk, P; Tropea, P; Tsirou, A; Veres, G I; Vichoudis, P; Voutilainen, M; Zeuner, W D; Bertl, W; Deiters, K; Erdmann, W; Gabathuler, K; Horisberger, R; Ingram, Q; Kaestli, H C; König, S; Kotlinski, D; Langenegger, U; Meier, F; Renker, D; Rohe, T; Sibille, J; Starodumov, A; Caminada, L; Chen, Z; Cittolin, S; Dissertori, G; Dittmar, M; Eugster, J; Freudenreich, K; Grab, C; Hervé, A; Hintz, W; Lecomte, P; Lustermann, W; Marchica, C; Meridiani, P; Milenovic, P; Moortgat, F; Nardulli, A; Nessi-Tedaldi, F; Pape, L; Pauss, F; Punz, T; Rizzi, A; Ronga, F J; Sala, L; Sanchez, A K; Sawley, M-C; Schinzel, D; Sordini, V; Stieger, B; Tauscher, L; Thea, A; Theofilatos, K; Treille, D; Weber, M; Wehrli, L; Weng, J; Amsler, C; Chiochia, V; De Visscher, S; Ivova Rikova, M; Millan Mejias, B; Regenfus, C; Robmann, P; Rommerskirchen, T; Schmidt, A; Tsirigkas, D; Wilke, L; Chang, Y H; Chen, K H; Chen, W T; Go, A; Kuo, C M; Li, S W; Lin, W; Liu, M H; Lu, Y J; Wu, J H; Yu, S S; Bartalini, P; Chang, P; Chang, Y H; Chang, Y W; Chao, Y; Chen, K F; Hou, W-S; Hsiung, Y; Kao, K Y; Lei, Y J; Lin, S W; Lu, R-S; Shiu, J G; Tzeng, Y M; Ueno, K; Wang, C C; Wang, M; Wei, J T; Adiguzel, A; Ayhan, A; Bakirci, M N; Cerci, S; Demir, Z; Dozen, C; Dumanoglu, I; Eskut, E; Girgis, S; Gökbulut, G; Güler, Y; Gurpinar, E; Hos, I; Kangal, E E; Karaman, T; Kayis Topaksu, A; Nart, A; Onengüt, G; Ozdemir, K; Ozturk, S; Polatöz, A; Sahin, O; Sengul, O; Sogut, K; Tali, B; Topakli, H; Uzun, D; Vergili, L N; Vergili, M; Zorbilmez, C; Akin, I V; Aliev, T; Bilmis, S; Deniz, M; Gamsizkan, H; Guler, A M; Ocalan, K; Ozpineci, A; Serin, M; Sever, R; Surat, U E; Zeyrek, M; Deliomeroglu, M; Demir, D; Gülmez, E; Halu, A; Isildak, B; Kaya, M; Kaya, O; Ozbek, M; Ozkorucuklu, S; Sonmez, N; Levchuk, L; Bell, P; Bostock, F; Brooke, J J; Cheng, T L; Cussans, D; Frazier, R; Goldstein, J; Hansen, M; Heath, G P; Heath, H F; Hill, C; Huckvale, B; Jackson, J; Kreczko, L; Mackay, C K; Metson, S; Newbold, D M; Nirunpong, K; Smith, V J; Ward, S; Basso, L; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Camanzi, B; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Kennedy, B W; Olaiya, E; Radburn-Smith, B C; Shepherd-Themistocleous, C H; Tomalin, I R; Womersley, W J; Worm, S D; Bainbridge, R; Ball, G; Ballin, J; Beuselinck, R; Buchmuller, O; Colling, D; Cripps, N; Cutajar, M; Davies, G; Della Negra, M; Foudas, C; Fulcher, J; Futyan, D; Guneratne Bryer, A; Hall, G; Hatherell, Z; Hays, J; Iles, G; Karapostoli, G; Lyons, L; Magnan, A-M; Marrouche, J; Nandi, R; Nash, J; Nikitenko, A; Papageorgiou, A; Pesaresi, M; Petridis, K; Pioppi, M; Raymond, D M; Rompotis, N; Rose, A; Ryan, M J; Seez, C; Sharp, P; Sparrow, A; Stoye, M; Tapper, A; Tourneur, S; Vazquez Acosta, M; Virdee, T; Wakefield, S; Wardrope, D; Whyntie, T; Barrett, M; Chadwick, M; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leslie, D; Reid, I D; Teodorescu, L; Bose, T; Clough, A; Heister, A; St John, J; Lawson, P; Lazic, D; Rohlf, J; Sulak, L; Andrea, J; Avetisyan, A; Bhattacharya, S; Chou, J P; Cutts, D; Esen, S; Heintz, U; Jabeen, S; Kukartsev, G; Landsberg, G; Narain, M; Nguyen, D; Speer, T; Tsang, K V; Borgia, M A; Breedon, R; Calderon De La Barca Sanchez, M; Cebra, D; Chertok, M; Conway, J; Cox, P T; Dolen, J; Erbacher, R; Friis, E; Ko, W; Kopecky, A; Lander, R; Liu, H; Maruyama, S; Miceli, T; Nikolic, M; Pellett, D; Robles, J; Schwarz, T; Searle, M; Smith, J; Squires, M; Tripathi, M; Vasquez Sierra, R; Veelken, C; Andreev, V; Arisaka, K; Cline, D; Cousins, R; Deisher, A; Erhan, S; Farrell, C; Felcini, M; Hauser, J; Ignatenko, M; Jarvis, C; Plager, C; Rakness, G; Schlein, P; Tucker, J; Valuev, V; Wallny, R; Babb, J; Clare, R; Ellison, J; Gary, J W; Hanson, G; Jeng, G Y; Kao, S C; Liu, F; Liu, H; Luthra, A; Nguyen, H; Pasztor, G; Satpathy, A; Shen, B C; Stringer, R; Sturdy, J; Sumowidagdo, S; Wilken, R; Wimpenny, S; Andrews, W; Branson, J G; Dusinberre, E; Evans, D; Golf, F; Holzner, A; Kelley, R; Lebourgeois, M; Letts, J; Mangano, B; Muelmenstaedt, J; Padhi, S; Palmer, C; Petrucciani, G; Pi, H; Pieri, M; Ranieri, R; Sani, M; Sharma, V; Simon, S; Tu, Y; Vartak, A; Würthwein, F; Yagil, A; Barge, D; Blume, M; Campagnari, C; D'Alfonso, M; Danielson, T; Garberson, J; Incandela, J; Justus, C; Kalavase, P; Koay, S A; Kovalskyi, D; Krutelyov, V; Lamb, J; Lowette, S; Pavlunin, V; Rebassoo, F; Ribnik, J; Richman, J; Rossin, R; Stuart, D; To, W; Vlimant, J R; Witherell, M; Bornheim, A; Bunn, J; Gataullin, M; Kcira, D; Litvine, V; Ma, Y; Newman, H B; Rogan, C; Shin, K; Timciuc, V; Veverka, J; Wilkinson, R; Yang, Y; Zhu, R Y; Akgun, B; Carroll, R; Ferguson, T; Jang, D W; Jun, S Y; Paulini, M; Russ, J; Terentyev, N; Vogel, H; Vorobiev, I; Cumalat, J P; Dinardo, M E; Drell, B R; Ford, W T; Heyburn, B; Luiggi Lopez, E; Nauenberg, U; Smith, J G; Stenson, K; Ulmer, K A; Wagner, S R; Zang, S L; Agostino, L; Alexander, J; Blekman, F; Chatterjee, A; Das, S; Eggert, N; Fields, L J; Gibbons, L K; Heltsley, B; Hopkins, W; Khukhunaishvili, A; Kreis, B; Kuznetsov, V; Kaufman, G Nicolas; Patterson, J R; Puigh, D; Riley, D; Ryd, A; Shi, X; Sun, W; Teo, W D; Thom, J; Thompson, J; Vaughan, J; Weng, Y; Wittich, P; Biselli, A; Cirino, G; Winn, D; Abdullin, S; Albrow, M; Anderson, J; Apollinari, G; Atac, M; Bakken, J A; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bloch, I; Borcherding, F; Burkett, K; Butler, J N; Chetluru, V; Cheung, H W K; Chlebana, F; Cihangir, S; Demarteau, M; Eartly, D P; Elvira, V D; Fisk, I; Freeman, J; Gao, Y; Gottschalk, E; Green, D; Gutsche, O; Hahn, A; Hanlon, J; Harris, R M; James, E; Jensen, H; Johnson, M; Joshi, U; Khatiwada, R; Kilminster, B; Klima, B; Kousouris, K; Kunori, S; Kwan, S; Limon, P; Lipton, R; Lykken, J; Maeshima, K; Marraffino, J M; Mason, D; McBride, P; McCauley, T; Miao, T; Mishra, K; Mrenna, S; Musienko, Y; Newman-Holmes, C; O'Dell, V; Popescu, S; Pordes, R; Prokofyev, O; Saoulidou, N; Sexton-Kennedy, E; Sharma, S; Smith, R P; Soha, A; Spalding, W J; Spiegel, L; Tan, P; Taylor, L; Tkaczyk, S; Uplegger, L; Vaandering, E W; Vidal, R; Whitmore, J; Wu, W; Yumiceva, F; Yun, J C; Acosta, D; Avery, P; Bourilkov, D; Chen, M; Di Giovanni, G P; Dobur, D; Drozdetskiy, A; Field, R D; Fu, Y; Furic, I K; Gartner, J; Kim, B; Klimenko, S; Konigsberg, J; Korytov, A; Kotov, K; Kropivnitskaya, A; Kypreos, T; Matchev, K; Mitselmakher, G; Pakhotin, Y; Piedra Gomez, J; Prescott, C; Remington, R; Schmitt, M; Scurlock, B; Sellers, P; Wang, D; Yelton, J; Zakaria, M; Ceron, C; Gaultney, V; Kramer, L; Lebolo, L M; Linn, S; Markowitz, P; Martinez, G; Mesa, D; Rodriguez, J L; Adams, T; Askew, A; Chen, J; Diamond, B; Gleyzer, S V; Haas, J; Hagopian, S; Hagopian, V; Jenkins, M; Johnson, K F; Prosper, H; Sekmen, S; Veeraraghavan, V; Baarmand, M M; Guragain, S; Hohlmann, M; Kalakhety, H; Mermerkaya, H; Ralich, R; Vodopiyanov, I; Adams, M R; Anghel, I M; Apanasevich, L; Bazterra, V E; Betts, R R; Callner, J; Cavanaugh, R; Dragoiu, C; Garcia-Solis, E J; Gerber, C E; Hofman, D J; Khalatian, S; Lacroix, F; Shabalina, E; Smoron, A; Strom, D; Varelas, N; Akgun, U; Albayrak, E A; Bilki, B; Cankocak, K; Clarida, W; Duru, F; Lae, C K; McCliment, E; Merlo, J-P; Mestvirishvili, A; Moeller, A; Nachtman, J; Newsom, C R; Norbeck, E; Olson, J; Onel, Y; Ozok, F; Sen, S; Wetzel, J; Yetkin, T; Yi, K; Barnett, B A; Blumenfeld, B; Bonato, A; Eskew, C; Fehling, D; Giurgiu, G; Gritsan, A V; Guo, Z J; Hu, G; Maksimovic, P; Rappoccio, S; Swartz, M; Tran, N V; Whitbeck, A; Baringer, P; Bean, A; Benelli, G; Grachov, O; Murray, M; Radicci, V; Sanders, S; Wood, J S; Zhukova, V; Bandurin, D; Bolton, T; Chakaberia, I; Ivanov, A; Kaadze, K; Maravin, Y; Shrestha, S; Svintradze, I; Wan, Z; Gronberg, J; Lange, D; Wright, D; Baden, D; Boutemeur, M; Eno, S C; Ferencek, D; Hadley, N J; Kellogg, R G; Kirn, M; Mignerey, A; Rossato, K; Rumerio, P; Santanastasio, F; Skuja, A; Temple, J; Tonjes, M B; Tonwar, S C; Twedt, E; Alver, B; Bauer, G; Bendavid, J; Busza, W; Butz, E; Cali, I A; Chan, M; D'Enterria, D; Everaerts, P; Gomez Ceballos, G; Goncharov, M; Hahn, K A; Harris, P; Kim, Y; Klute, M; Lee, Y-J; Li, W; Loizides, C; Luckey, P D; Ma, T; Nahn, S; Paus, C; Roland, C; Roland, G; Rudolph, M; Stephans, G S F; Sumorok, K; Sung, K; Wenger, E A; Wyslouch, B; Xie, S; Yilmaz, Y; Yoon, A S; Zanetti, M; Cole, P; Cooper, S I; Cushman, P; Dahmes, B; De Benedetti, A; Dudero, P R; Franzoni, G; Haupt, J; Klapoetke, K; Kubota, Y; Mans, J; Petyt, D; Rekovic, V; Rusack, R; Sasseville, M; Singovsky, A; Cremaldi, L M; Godang, R; Kroeger, R; Perera, L; Rahmat, R; Sanders, D A; Sonnek, P; Summers, D; Bloom, K; Bose, S; Butt, J; Claes, D R; Dominguez, A; Eads, M; Keller, J; Kelly, T; Kravchenko, I; Lazo-Flores, J; Lundstedt, C; Malbouisson, H; Malik, S; Snow, G R; Baur, U; Iashvili, I; Kharchilava, A; Kumar, A; Smith, K; Strang, M; Zennamo, J; Alverson, G; Barberis, E; Baumgartel, D; Boeriu, O; Reucroft, S; Swain, J; Wood, D; Zhang, J; Anastassov, A; Kubik, A; Ofierzynski, R A; Pozdnyakov, A; Schmitt, M; Stoynev, S; Velasco, M; Won, S; Antonelli, L; Berry, D; Hildreth, M; Jessop, C; Karmgard, D J; Kolb, J; Kolberg, T; Lannon, K; Lynch, S; Marinelli, N; Morse, D M; Ruchti, R; Slaunwhite, J; Valls, N; Warchol, J; Wayne, M; Ziegler, J; Bylsma, B; Durkin, L S; Gu, J; Killewald, P; Ling, T Y; Williams, G; Adam, N; Berry, E; Elmer, P; Gerbaudo, D; Halyo, V; Hunt, A; Jones, J; Laird, E; Lopes Pegna, D; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Piroué, P; Stickland, D; Tully, C; Werner, J S; Zuranski, A; Acosta, J G; Huang, X T; Lopez, A; Mendez, H; Oliveros, S; Ramirez Vargas, J E; Zatzerklyaniy, A; Alagoz, E; Barnes, V E; Bolla, G; Borrello, L; Bortoletto, D; Everett, A; Garfinkel, A F; Gecse, Z; Gutay, L; Jones, M; Koybasi, O; Laasanen, A T; Leonardo, N; Liu, C; Maroussov, V; Merkel, P; Miller, D H; Neumeister, N; Potamianos, K; Shipsey, I; Silvers, D; Yoo, H D; Zablocki, J; Zheng, Y; Jindal, P; Parashar, N; Cuplov, V; Ecklund, K M; Geurts, F J M; Liu, J H; Morales, J; Padley, B P; Redjimi, R; Roberts, J; Betchart, B; Bodek, A; Chung, Y S; de Barbaro, P; Demina, R; Flacher, H; Garcia-Bellido, A; Gotra, Y; Han, J; Harel, A; Miner, D C; Orbaker, D; Petrillo, G; Vishnevskiy, D; Zielinski, M; Bhatti, A; Demortier, L; Goulianos, K; Hatakeyama, K; Lungu, G; Mesropian, C; Yan, M; Atramentov, O; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Hits, D; Lath, A; Rose, K; Schnetzer, S; Somalwar, S; Stone, R; Thomas, S; Cerizza, G; Hollingsworth, M; Spanier, S; Yang, Z C; York, A; Asaadi, J; Eusebi, R; Gilmore, J; Gurrola, A; Kamon, T; Khotilovich, V; Montalvo, R; Nguyen, C N; Pivarski, J; Safonov, A; Sengupta, S; Toback, D; Weinberger, M; Akchurin, N; Bardak, C; Damgov, J; Jeong, C; Kovitanggoon, K; Lee, S W; Mane, P; Roh, Y; Sill, A; Volobouev, I; Wigmans, R; Yazgan, E; Appelt, E; Brownson, E; Engh, D; Florez, C; Gabella, W; Johns, W; Kurt, P; Maguire, C; Melo, A; Sheldon, P; Velkovska, J; Arenton, M W; Balazs, M; Buehler, M; Conetti, S; Cox, B; Hirosky, R; Ledovskoy, A; Neu, C; Yohay, R; Gollapinni, S; Gunthoti, K; Harr, R; Karchin, P E; Mattson, M; Milstène, C; Sakharov, A; Anderson, M; Bachtis, M; Bellinger, J N; Carlsmith, D; Dasu, S; Dutta, S; Efron, J; Gray, L; Grogg, K S; Grothe, M; Hall-Wilton, R; Herndon, M; Klabbers, P; Klukas, J; Lanaro, A; Lazaridis, C; Leonard, J; Lomidze, D; Loveless, R; Mohapatra, A; Polese, G; Reeder, D; Savin, A; Smith, W H; Swanson, J; Weinberg, M

2010-07-09

Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at square root of s = 7  TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dN(ch)/dη|(|η|<0.5) = 5.78 ± 0.01(stat) ± 0.23(syst) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from square root of s = 0.9 to 7 TeV is [66.1 ± 1.0(stat) ± 4.2(syst)]%. The mean transverse momentum is measured to be 0.545 ± 0.005(stat) ± 0.015(syst)  GeV/c. The results are compared with similar measurements at lower energies.

Leaf Chlorophyll Content Estimation of Winter Wheat Based on Visible and Near-Infrared Sensors.

PubMed

Zhang, Jianfeng; Han, Wenting; Huang, Lvwen; Zhang, Zhiyong; Ma, Yimian; Hu, Yamin

2016-03-25

The leaf chlorophyll content is one of the most important factors for the growth of winter wheat. Visual and near-infrared sensors are a quick and non-destructive testing technology for the estimation of crop leaf chlorophyll content. In this paper, a new approach is developed for leaf chlorophyll content estimation of winter wheat based on visible and near-infrared sensors. First, the sliding window smoothing (SWS) was integrated with the multiplicative scatter correction (MSC) or the standard normal variable transformation (SNV) to preprocess the reflectance spectra images of wheat leaves. Then, a model for the relationship between the leaf relative chlorophyll content and the reflectance spectra was developed using the partial least squares (PLS) and the back propagation neural network. A total of 300 samples from areas surrounding Yangling, China, were used for the experimental studies. The samples of visible and near-infrared spectroscopy at the wavelength of 450,900 nm were preprocessed using SWS, MSC and SNV. The experimental results indicate that the preprocessing using SWS and SNV and then modeling using PLS can achieve the most accurate estimation, with the correlation coefficient at 0.8492 and the root mean square error at 1.7216. Thus, the proposed approach can be widely used for winter wheat chlorophyll content analysis.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

Measurement of 3-D Vibrational Motion by Dynamic Photogrammetry Using Least-Square Image Matching for Sub-Pixel Targeting to Improve Accuracy.

PubMed

Lee, Hyoseong; Rhee, Huinam; Oh, Jae Hong; Park, Jin Ho

2016-03-11

This paper deals with an improved methodology to measure three-dimensional dynamic displacements of a structure by digital close-range photogrammetry. A series of stereo images of a vibrating structure installed with targets are taken at specified intervals by using two daily-use cameras. A new methodology is proposed to accurately trace the spatial displacement of each target in three-dimensional space. This method combines the correlation and the least-square image matching so that the sub-pixel targeting can be obtained to increase the measurement accuracy. Collinearity and space resection theory are used to determine the interior and exterior orientation parameters. To verify the proposed method, experiments have been performed to measure displacements of a cantilevered beam excited by an electrodynamic shaker, which is vibrating in a complex configuration with mixed bending and torsional motions simultaneously with multiple frequencies. The results by the present method showed good agreement with the measurement by two laser displacement sensors. The proposed methodology only requires inexpensive daily-use cameras, and can remotely detect the dynamic displacement of a structure vibrating in a complex three-dimensional defection shape up to sub-pixel accuracy. It has abundant potential applications to various fields, e.g., remote vibration monitoring of an inaccessible or dangerous facility.

Measurement of 3-D Vibrational Motion by Dynamic Photogrammetry Using Least-Square Image Matching for Sub-Pixel Targeting to Improve Accuracy

PubMed Central

Lee, Hyoseong; Rhee, Huinam; Oh, Jae Hong; Park, Jin Ho

2016-01-01

This paper deals with an improved methodology to measure three-dimensional dynamic displacements of a structure by digital close-range photogrammetry. A series of stereo images of a vibrating structure installed with targets are taken at specified intervals by using two daily-use cameras. A new methodology is proposed to accurately trace the spatial displacement of each target in three-dimensional space. This method combines the correlation and the least-square image matching so that the sub-pixel targeting can be obtained to increase the measurement accuracy. Collinearity and space resection theory are used to determine the interior and exterior orientation parameters. To verify the proposed method, experiments have been performed to measure displacements of a cantilevered beam excited by an electrodynamic shaker, which is vibrating in a complex configuration with mixed bending and torsional motions simultaneously with multiple frequencies. The results by the present method showed good agreement with the measurement by two laser displacement sensors. The proposed methodology only requires inexpensive daily-use cameras, and can remotely detect the dynamic displacement of a structure vibrating in a complex three-dimensional defection shape up to sub-pixel accuracy. It has abundant potential applications to various fields, e.g., remote vibration monitoring of an inaccessible or dangerous facility. PMID:26978366

Toxicity of ionic liquids: database and prediction via quantitative structure-activity relationship method.

PubMed

Zhao, Yongsheng; Zhao, Jihong; Huang, Ying; Zhou, Qing; Zhang, Xiangping; Zhang, Suojiang

2014-08-15

A comprehensive database on toxicity of ionic liquids (ILs) is established. The database includes over 4000 pieces of data. Based on the database, the relationship between IL's structure and its toxicity has been analyzed qualitatively. Furthermore, Quantitative Structure-Activity relationships (QSAR) model is conducted to predict the toxicities (EC50 values) of various ILs toward the Leukemia rat cell line IPC-81. Four parameters selected by the heuristic method (HM) are used to perform the studies of multiple linear regression (MLR) and support vector machine (SVM). The squared correlation coefficient (R(2)) and the root mean square error (RMSE) of training sets by two QSAR models are 0.918 and 0.959, 0.258 and 0.179, respectively. The prediction R(2) and RMSE of QSAR test sets by MLR model are 0.892 and 0.329, by SVM model are 0.958 and 0.234, respectively. The nonlinear model developed by SVM algorithm is much outperformed MLR, which indicates that SVM model is more reliable in the prediction of toxicity of ILs. This study shows that increasing the relative number of O atoms of molecules leads to decrease in the toxicity of ILs. Copyright © 2014 Elsevier B.V. All rights reserved.

[Characteristic wavelengths selection of soluble solids content of pear based on NIR spectral and LS-SVM].

PubMed

Fan, Shu-xiang; Huang, Wen-qian; Li, Jiang-bo; Zhao, Chun-jiang; Zhang, Bao-hua

2014-08-01

To improve the precision and robustness of the NIR model of the soluble solid content (SSC) on pear. The total number of 160 pears was for the calibration (n=120) and prediction (n=40). Different spectral pretreatment methods, including standard normal variate (SNV) and multiplicative scatter correction (MSC) were used before further analysis. A combination of genetic algorithm (GA) and successive projections algorithm (SPA) was proposed to select most effective wavelengths after uninformative variable elimination (UVE) from original spectra, SNV pretreated spectra and MSC pretreated spectra respectively. The selected variables were used as the inputs of least squares-support vector machine (LS-SVM) model to build models for de- termining the SSC of pear. The results indicated that LS-SVM model built using SNVE-UVE-GA-SPA on 30 characteristic wavelengths selected from full-spectrum which had 3112 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.956, 0.271 for SSC. The model is reliable and the predicted result is effective. The method can meet the requirement of quick measuring SSC of pear and might be important for the development of portable instruments and online monitoring.

Development and evaluation of social cognitive measures related to adolescent physical activity.

PubMed

Dewar, Deborah L; Lubans, David Revalds; Morgan, Philip James; Plotnikoff, Ronald C

2013-05-01

This study aimed to develop and evaluate the construct validity and reliability of modernized social cognitive measures relating to physical activity behaviors in adolescents. An instrument was developed based on constructs from Bandura's Social Cognitive Theory and included the following scales: self-efficacy, situation (perceived physical environment), social support, behavioral strategies, and outcome expectations and expectancies. The questionnaire was administered in a sample of 171 adolescents (age = 13.6 ± 1.2 years, females = 61%). Confirmatory factor analysis was employed to examine model-fit for each scale using multiple indices, including chi-square index, comparative-fit index (CFI), goodness-of-fit index (GFI), and the root mean square error of approximation (RMSEA). Reliability properties were also examined (ICC and Cronbach's alpha). Each scale represented a statistically sound measure: fit indices indicated each model to be an adequate-to-exact fit to the data; internal consistency was acceptable to good (α = 0.63-0.79); rank order repeatability was strong (ICC = 0.82-0.91). Results support the validity and reliability of social cognitive scales relating to physical activity among adolescents. As such, the developed scales have utility for the identification of potential social cognitive correlates of youth physical activity, mediators of physical activity behavior changes and the testing of theoretical models based on Social Cognitive Theory.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network.

PubMed

Liu, Ruixin; Zhang, Xiaodong; Zhang, Lu; Gao, Xiaojie; Li, Huiling; Shi, Junhan; Li, Xuelin

2014-06-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network

PubMed Central

LIU, RUIXIN; ZHANG, XIAODONG; ZHANG, LU; GAO, XIAOJIE; LI, HUILING; SHI, JUNHAN; LI, XUELIN

2014-01-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue. PMID:24926369

Azimuthal anisotropy and correlations at large transverse momenta in p + p and Au + Au collisions at square root sNN=200 GeV.

PubMed

Adams, J; Aggarwal, M M; Ahammed, Z; Amonett, J; Anderson, B D; Arkhipkin, D; Averichev, G S; Badyal, S K; Bai, Y; Balewski, J; Barannikova, O; Barnby, L S; Baudot, J; Bekele, S; Belaga, V V; Bellwied, R; Berger, J; Bezverkhny, B I; Bharadwaj, S; Bhasin, A; Bhati, A K; Bhatia, V S; Bichsel, H; Billmeier, A; Bland, L C; Blyth, C O; Bonner, B E; Botje, M; Boucham, A; Brandin, A V; Bravar, A; Bystersky, M; Cadman, R V; Cai, X Z; Caines, H; Calderón de la Barca Sánchez, M; Carroll, J; Castillo, J; Cebra, D; Chajecki, Z; Chaloupka, P; Chattopdhyay, S; Chen, H F; Chen, Y; Cheng, J; Cherney, M; Chikanian, A; Christie, W; Coffin, J P; Cormier, T M; Cramer, J G; Crawford, H J; Das, D; Das, S; de Moura, M M; Derevschikov, A A; Didenko, L; Dietel, T; Dogra, S M; Dong, W J; Dong, X; Draper, J E; Du, F; Dubey, A K; Dunin, V B; Dunlop, J C; Dutta Mazumdar, M R; Eckardt, V; Edwards, W R; Efimov, L G; Emelianov, V; Engelage, J; Eppley, G; Erazmus, B; Estienne, M; Fachini, P; Faivre, J; Fatemi, R; Fedorisin, J; Filimonov, K; Filip, P; Finch, E; Fine, V; Fisyak, Y; Foley, K J; Fomenko, K; Fu, J; Gagliardi, C A; Gans, J; Ganti, M S; Gaudichet, L; Geurts, F; Ghazikhanian, V; Ghosh, P; Gonzalez, J E; Grachov, O; Grebenyuk, O; Grosnick, D; Guertin, S M; Guo, Y; Gupta, A; Gutierrez, T D; Hallman, T J; Hamed, A; Hardtke, D; Harris, J W; Heinz, M; Henry, T W; Hepplemann, S; Hippolyte, B; Hirsch, A; Hjort, E; Hoffmann, G W; Huang, H Z; Huang, S L; Hughes, E W; Humanic, T J; Igo, G; Ishihara, A; Jacobs, P; Jacobs, W W; Janik, M; Jiang, H; Jones, P G; Judd, E G; Kabana, S; Kang, K; Kaplan, M; Keane, D; Khodyrev, V Yu; Kiryluk, J; Kisiel, A; Kislov, E M; Klay, J; Klein, S R; Klyachko, A; Koetke, D D; Kollegger, T; Kopytine, M; Kotchenda, L; Kramer, M; Kravtsov, P; Kravtsov, V I; Krueger, K; Kuhn, C; Kulikov, A I; Kumar, A; Kunz, C L; Kutuev, R Kh; Kuznetsov, A A; Lamont, M A C; Landgraf, J M; Lange, S; Laue, F; Lauret, J; Lebedev, A; Lednicky, R; Lehocka, S; LeVine, M J; Li, C; Li, Q; Li, Y; Lindenbaum, S J; Lisa, M A; Liu, F; Liu, L; Liu, Q J; Liu, Z; Ljubicic, T; Llope, W J; Long, H; Longacre, R S; Lopez-Noriega, M; Love, W A; Lu, Y; Ludlam, T; Lynn, D; Ma, G L; Ma, J G; Ma, Y G; Magestro, D; Mahajan, S; Mahapatra, D P; Majka, R; Mangotra, L K; Manweiler, R; Margetis, S; Markert, C; Martin, L; Marx, J N; Matis, H S; Matulenko, Yu A; McClain, C J; McShane, T S; Meissner, F; Melnick, Yu; Meschanin, A; Miller, M L; Milosevich, Z; Minaev, N G; Mironov, C; Mischke, A; Mishra, D K; Mitchell, J; Mohanty, B; Molnar, L; Moore, C F; Morozov, D A; Munhoz, M G; Nandi, B K; Nayak, S K; Nayak, T K; Nelson, J M; Netrakanti, P K; Nikitin, V A; Nogach, L V; Nurushev, S B; Odyniec, G; Ogawa, A; Okorokov, V; Oldenburg, M; Olson, D; Pal, S K; Panebratsev, Y; Panitkin, S Y; Pavlinov, A I; Pawlak, T; Peitzmann, T; Perevoztchikov, V; Perkins, C; Peryt, W; Petrov, V A; Phatak, S C; Picha, R; Planinic, M; Pluta, J; Porile, N; Porter, J; Poskanzer, A M; Potekhin, M; Potrebenikova, E; Potukuchi, B V K S; Prindle, D; Pruneau, C; Putschke, J; Rai, G; Rakness, G; Raniwala, R; Raniwala, S; Ravel, O; Ray, R L; Razin, S V; Reichhold, D; Reid, J G; Renault, G; Retiere, F; Ridiger, A; Ritter, H G; Roberts, J B; Rogachevskiy, O V; Romero, J L; Rose, A; Roy, C; Ruan, L; Sahoo, R; Sakrejda, I; Salur, S; Sandweiss, J; Savin, I; Sazhin, P S; Schambach, J; Scharenberg, R P; Schmitz, N; Schroeder, L S; Schweda, K; Seger, J; Seyboth, P; Shahaliev, E; Shao, M; Shao, W; Sharma, M; Shen, W Q; Shestermanov, K E; Shimanskiy, S S; Sichtermann, E; Simon, F; Singaraju, R N; Skoro, G; Smirnov, N; Snellings, R; Sood, G; Sorensen, P; Sowinski, J; Speltz, J; Spinka, H M; Srivastava, B; Stadnik, A; Stanislaus, T D S; Stock, R; Stolpovsky, A; Strikhanov, M; Stringfellow, B; Suaide, A A P; Sugarbaker, E; Suire, C; Sumbera, M; Surrow, B; Symons, T J M; Szanto de Toledo, A; Szarwas, P; Tai, A; Takahashi, J; Tang, A H; Tarnowsky, T; Thein, D; Thomas, J H; Timoshenko, S; Tokarev, M; Trentalange, S; Tribble, R E; Tsai, O D; Ulery, J; Ullrich, T; Underwood, D G; Urkinbaev, A; Van Buren, G; van Leeuwen, M; Vander Molen, A M; Varma, R; Vasilevski, I M; Vasiliev, A N; Vernet, R; Vigdor, S E; Viyogi, Y P; Vokal, S; Voloshin, S A; Vznuzdaev, M; Waggoner, W T; Wang, F; Wang, G; Wang, G; Wang, X L; Wang, Y; Wang, Y; Wang, Z M; Ward, H; Watson, J W; Webb, J C; Wells, R; Westfall, G D; Wetzler, A; Whitten, C; Wieman, H; Wissink, S W; Witt, R; Wood, J; Wu, J; Xu, N; Xu, Z; Xu, Z Z; Yamamoto, E; Yepes, P; Yurevich, V I; Zanevsky, Y V; Zhang, H; Zhang, W M; Zhang, Z P; Zolnierczuk, P A; Zoulkarneev, R; Zoulkarneeva, Y; Zubarev, A N

2004-12-17

Results on high transverse momentum charged particle emission with respect to the reaction plane are presented for Au + Au collisions at square root s(NN)=200 GeV. Two- and four-particle correlations results are presented as well as a comparison of azimuthal correlations in Au + Au collisions to those in p + p at the same energy. The elliptic anisotropy v(2) is found to reach its maximum at p(t) approximately 3 GeV/c, then decrease slowly and remain significant up to p(t) approximately 7-10 GeV/c. Stronger suppression is found in the back-to-back high-p(t) particle correlations for particles emitted out of plane compared to those emitted in plane. The centrality dependence of v(2) at intermediate p(t) is compared to simple models based on jet quenching.

On some labelings of triangular snake and central graph of triangular snake graph

NASA Astrophysics Data System (ADS)

Agasthi, P.; Parvathi, N.

2018-04-01

A Triangular snake Tn is obtained from a path u 1 u 2 … u n by joining ui and u i+1 to a new vertex wi for 1≤i≤n‑1. A Central graph of Triangular snake C(T n ) is obtained by subdividing each edge of Tn exactly once and joining all the non adjacent vertices of Tn . In this paper the ways to construct square sum, square difference, Root Mean square, strongly Multiplicative, Even Mean and Odd Mean labeling for Triangular Snake and Central graph of Triangular Snake graphs are reported.

[Relationship between vibratory sense threshold and blood lead concentration in ceramic color workers and transfer printing manufacturers].

PubMed

Fukaya, Y; Matsumoto, T; Fujiwara, N; Tokudome, S

1995-08-01

We measured vibratory sense thresholds (VSTs) at 63Hz and 125Hz on the third fingertip of the right hand and on the third toe of the right foot of 74 male workers. The subjects were workers engaged in manufacturing ceramic color and transfer printing paper, whose blood lead (Pb-B) levels were 2-58 micrograms/dl. They were divided into three groups according to the Pb-B levels, namely, below 9, 10-19, and 20 micrograms/dl or more. For statistical analysis, simple and partial correlations, and Scheffé's multiple comparison between the least squares means were used. The VSTs on the fingertip as well as on the toe showed a significant correlation with age. The VSTs at 125Hz on the fingertip were also significantly correlated with alcohol consumption and cigarette smoking. Controlling for age, systolic blood pressure, alcohol consumption and smoking habit, a significant dose-effect relationship was observed between the VSTs at not only 63Hz but at 125Hz on the fingertip, and each of the corresponding Pb-B levels. A similar tendency was also observed at the two frequencies on the toe. The measurement of VSTs was considered to be an effective screening test for sensory nerve disorders caused by lead poisoning.

Cooling of High Pressure Rocket Thrust Chambers with Liquid Oxygen

NASA Technical Reports Server (NTRS)

Price, H. G.

1980-01-01

An experimental program using hydrogen and oxygen as the propellants and supercritical liquid oxygen (LOX) as the coolant was conducted at 4.14 and 8.274 MN/square meters (600 and 1200 psia) chamber pressure. Data on the following are presented: the effect of LOX leaking into the combustion region through small cracks in the chamber wall; and verification of the supercritical oxygen heat transfer correlation developed from heated tube experiments; A total of four thrust chambers with throat diameters of 0.066 m were tested. Of these, three were cyclically tested to 4.14 MN/square meters (600 psia) chamber pressure until a crack developed. One had 23 additional hot cycles accumulated with no apparent metal burning or distress. The fourth chamber was operated at 8.274 MN/square meters (1200 psia) pressure to obtain steady state heat transfer data. Wall temperature measurements confirmed the heat transfer correlation.

Clustering "N" Objects into "K" Groups under Optimal Scaling of Variables.

ERIC Educational Resources Information Center

van Buuren, Stef; Heiser, Willem J.

1989-01-01

A method based on homogeneity analysis (multiple correspondence analysis or multiple scaling) is proposed to reduce many categorical variables to one variable with "k" categories. The method is a generalization of the sum of squared distances cluster analysis problem to the case of mixed measurement level variables. (SLD)

The bilinear complexity and practical algorithms for matrix multiplication

NASA Astrophysics Data System (ADS)

Smirnov, A. V.

2013-12-01

A method for deriving bilinear algorithms for matrix multiplication is proposed. New estimates for the bilinear complexity of a number of problems of the exact and approximate multiplication of rectangular matrices are obtained. In particular, the estimate for the boundary rank of multiplying 3 × 3 matrices is improved and a practical algorithm for the exact multiplication of square n × n matrices is proposed. The asymptotic arithmetic complexity of this algorithm is O( n 2.7743).

Weighted least-square approach for simultaneous measurement of multiple reflective surfaces

NASA Astrophysics Data System (ADS)

Tang, Shouhong; Bills, Richard E.; Freischlad, Klaus

2007-09-01

Phase shifting interferometry (PSI) is a highly accurate method for measuring the nanometer-scale relative surface height of a semi-reflective test surface. PSI is effectively used in conjunction with Fizeau interferometers for optical testing, hard disk inspection, and semiconductor wafer flatness. However, commonly-used PSI algorithms are unable to produce an accurate phase measurement if more than one reflective surface is present in the Fizeau interferometer test cavity. Examples of test parts that fall into this category include lithography mask blanks and their protective pellicles, and plane parallel optical beam splitters. The plane parallel surfaces of these parts generate multiple interferograms that are superimposed in the recording plane of the Fizeau interferometer. When using wavelength shifting in PSI the phase shifting speed of each interferogram is proportional to the optical path difference (OPD) between the two reflective surfaces. The proposed method is able to differentiate each underlying interferogram from each other in an optimal manner. In this paper, we present a method for simultaneously measuring the multiple test surfaces of all underlying interferograms from these superimposed interferograms through the use of a weighted least-square fitting technique. The theoretical analysis of weighted least-square technique and the measurement results will be described in this paper.

The Impact of School Socioeconomic Status on Student-Generated Teacher Ratings

ERIC Educational Resources Information Center

Agnew, Steve

2011-01-01

This paper uses ordinary least squares, logit and probit regressions, along with chi-square analysis applied to nationwide data from the New Zealand ratemyteacher website to establish if there is any correlation between student ratings of their teachers and the socioeconomic status of the school the students attend. The results show that students…

Meta-Analytic Structural Equation Modeling: A Two-Stage Approach

ERIC Educational Resources Information Center

Cheung, Mike W. L.; Chan, Wai

2005-01-01

To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc…

The Robustness of LISREL Estimates in Structural Equation Models with Categorical Variables.

ERIC Educational Resources Information Center

Ethington, Corinna A.

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…

Biomarkers of One-Carbon Metabolism Are Associated with Biomarkers of Inflammation in Women123

PubMed Central

Abbenhardt, Clare; Miller, Joshua W.; Song, Xiaoling; Brown, Elissa C.; Cheng, Ting-Yuan David; Wener, Mark H.; Zheng, Yingye; Toriola, Adetunji T.; Neuhouser, Marian L.; Beresford, Shirley A. A.; Makar, Karen W.; Bailey, Lynn B.; Maneval, David R.; Green, Ralph; Manson, JoAnn E.; Van Horn, Linda; Ulrich, Cornelia M.

2014-01-01

Folate-mediated one-carbon metabolism is essential for DNA synthesis, repair, and methylation. Perturbations in one-carbon metabolism have been implicated in increased risk of some cancers and may also affect inflammatory processes. We investigated these interrelated pathways to understand their relation. The objective was to explore associations between inflammation and biomarkers of nutritional status and one-carbon metabolism. In a cross-sectional study in 1976 women selected from the Women’s Health Initiative Observational Study, plasma vitamin B-6 [pyridoxal-5′-phosphate (PLP)], plasma vitamin B-12, plasma folate, and RBC folate were measured as nutritional biomarkers; serum C-reactive protein (CRP) and serum amyloid A (SAA) were measured as biomarkers of inflammation; and homocysteine and cysteine were measured as integrated biomarkers of one-carbon metabolism. Student’s t, chi-square, and Spearman rank correlations, along with multiple linear regressions, were used to explore relations between biomarkers; additionally, we tested stratification by folic acid fortification period and multivitamin use. With the use of univariate analysis, plasma PLP was the only nutritional biomarker that was modestly significantly correlated with serum CRP and SAA (ρ = −0.22 and −0.12, respectively; P < 0.0001). Homocysteine (μmol/L) showed significant inverse correlations with all nutritional biomarkers (ranging from ρ = −0.30 to ρ = −0.46; all P < 0.0001). With the use of multiple linear regression, plasma PLP, RBC folate, homocysteine, and cysteine were identified as independent predictors of CRP; and PLP, vitamin B-12, RBC folate, and homocysteine were identified as predictors of SAA. When stratified by folic acid fortification period, nutrition-homocysteine correlations were generally weaker in the postfortification period, whereas associations between plasma PLP and serum CRP increased. Biomarkers of inflammation are associated with PLP, RBC folate, and homocysteine in women. The connection between the pathways needs to be further investigated and causality established. The trial is registered at clinicaltrials.gov as NCT00000611. PMID:24647390

[Culture and quality of life assessment in Chinese populations].

PubMed

Xia, Ping; Li, Ning-Xiu; Liu, Chao-Jie; Lü, Yu-Bo; Zhang, Qiang; Ou, Ai-Hua

2010-07-01

To investigate the impact of cultural factors on quality of life (QOL) and to identify appropriate ways of dividing sub-populations for population norm-based quality of life assessment. The WHOQOL-BREF was used as a QOL instrument. Another questionnaire was developed to assess cultural values. A cross-sectional survey was undertaken in 1090 Guangzhou residents, which included 635 respondents from communities and 455 patients who visited outpatient departments of hospitals. Cronbach's a coefficients and item-domain correlation coefficients were calculated to test the reliability and validity of the WHOQOL-BREF, respectively. Student t test, ANOVA and stepwise multiple linear regression analysis were performed to identify the variables that might have an impact on the QOL. Two regression models with and without including cultural variables were constructed, and the extent of impact exerted by the cultural factors was assessed through a comparison of the change of adjusted R square values. A total of 1052 (96%) valid questionnaire were returned. The Cronbach's alpha coefficients of the WHOQOL-BREF ranged from 0.67 to 0.78. Age, education, occupation and family income were correlated with all of the domains of the WHOQOL-BREF. Chronic condition was correlated with physical, psychological, and social relationship domains of the WHOQOL-BREF. Gender was correlated with physical and psychological domains of the WHOQOL-BREF. The multiple regression analysis showed that social and demographic factors contributed to 6.3%, 13.6%, 10.4% and 8.7% of the predicted variances for the physical, psychological, social relationship, and environment domains, respectively. Social support, horizontal collectivism, vertical individualism, escape acceptance, fear of death, health value, supernatural belief had a significant impact on QOL. However, social support was the only one factor that had an impact on all of the four QOL domains. It is necessary to divide sub-cultural populations for population norm-based QOL assessment. Further research is needed to develop a practical approach to the sub-cultural population division.

Association between diabetes-related factors and clinical periodontal parameters in type-2 diabetes mellitus.

PubMed

Kim, Eun-Kyong; Lee, Sang Gyu; Choi, Youn-Hee; Won, Kyu-Chang; Moon, Jun Sung; Merchant, Anwar T; Lee, Hee-Kyung

2013-11-07

Evidence consistently shows that diabetes is a risk factor for increased prevalence of gingivitis and periodontitis. But there is a controversy about the relationship between diabetes related factors and periodontal health. The aim of the present study is to explore the relationship between diabetes related factors such as glycosylated hemoglobin, fasting blood glucose, duration of diabetes and compliance to diabetes self management and periodontal health status. Periodontal health of 125 participants with type-2 diabetes mellitus was measured by the number of missing teeth, community periodontal index (CPI), Russell's periodontal index and papillary bleeding index. Information on sociodemographic factors, oral hygiene behavior, duration and compliance to self management of diabetes, levels of glycosylated hemoglobin(HbA1c) and fasting blood glucose(FBG) were collected by interview and hospital medical records. Statistically, independent t-test, an analysis of variance (ANOVA), chi-squared test and multiple regression analyses were used to assess the association between diabetes-related factors and periodontal health. Periodontal parameters including the number of missing teeth and papillary bleeding index were significantly influenced by duration of diabetes, FBG and compliance to self management of diabetes. CPI was significantly influenced by duration of diabetes, FBG and HbA1C. And Russell's periodontal index was significantly influenced by duration of diabetes, FBG, HbA1C and compliance to self management of diabetes. Results of multiple linear regression analysis showed that the duration of diabetes showed significant positive correlation with all of the periodontal health parameters, except for missing teeth. HbA1c was correlated with Russell's periodontal and papillary bleeding index. FBG and compliance to self management of diabetes were correlated with missing teeth and papillary bleeding index respectively. Diabetes-related factors such as duration of diabetes, FBG, HbA1c and compliance to self management of diabetes were significantly correlated with periodontal health among individuals with type-2 diabetes.

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

PubMed

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

Growth hormone responsiveness: peak stimulated growth hormone levels and other variables in idiopathic short stature (ISS): data from the National Cooperative Growth Study.

PubMed

Moore, Wayne V; Dana, Ken; Frane, James; Lippe, Barbara

2008-09-01

In children with idiopathic short stature (ISS), growth hormone (GH) response to a provocative test will be inversely related to the first year response to hGH and be a variable accounting for a degree of responsiveness. Because high levels of GH are a characteristic of GH insensitivity, such as in Laron syndrome, it is possible that a high stimulated GH is associated with a lower first year height velocity among children diagnosed as having ISS. We examined the relationship between the peak stimulated GH levels in 3 ISS groups; GH >10 -<25, 25-40, and >40 ng/mL and the first year growth response to rhGH therapy. We also looked at 8 other predictor variables (age, sex, height SDS, height age, body mass index (BMI), bone age, dose, and SDS deficit from target parental height. Multiple regression analysis with the first year height as the dependent variable and peak stimulated GH was the primary endpoint. The predictive value of adding each of the other variables was then assessed. Mean change in height velocity was similar among the three groups, with a maximum difference among the groups of 0.6 cm/yr. There was a small but statistically significant correlation (r=-0.12) between the stimulated GH and first year height velocity. The small correlation between first year growth response and peak GH is not clinically relevant in defining GH resistance. No cut off level by peak GH could be determined to enhance the usefulness of this measure to predict response. Baseline age was the only clinically significant predictor, R-squared, 6.4%. All other variables contributed less than an additional 2% to the R-squared.

Chinese Adaptation and Psychometric Properties of the Child Version of the Cognitive Emotion Regulation Questionnaire

PubMed Central

Liu, Wen; Chen, Liang; Blue, Philip R.

2016-01-01

This study aimed to validate a Chinese’s adaption of the Cognitive Emotion Regulation Questionnaire for children (CERQ-Ck). This self-report instrument evaluates nine cognitive emotion regulation strategies that can be used by children after experiencing a negative life event. The CERQ-Ck was evaluated in a sample of 1403 elementary students between the ages of 9 and 11 by using cluster sampling. All the item-correlation coefficients for CERQ-Ck were above 0.30. The internal consistencies of the nine factors suggested moderate reliability (0.66 to 0.73). Confirmatory factor analysis (CFA) indicated that the current version had the same structure as the original instrument (Tucker–Lewis index = 0.912, comparative fit index = 0.922, root mean square error of approximation = 0.032, standardized root mean square residual = 0.044). A second-order factor and a third-order factor structure were also found. Test–retest correlations (0.53 to 0.70, ps < 0.01) over a period of 1 month, which ranged from acceptable to moderately strong were obtained from a random and stratified subsample of elementary students (N = 76). In addition, we analyzed convergent validity in relation to CERQ-Ck and the Chinese version of the Children’s Depression Inventory model dimensions with a subsample of 1083 elementary students. Multiple-group CFA confirmed the measurement invariance for both the male and female groups (ΔCFI < 0.01, ΔRMSEA < 0.015). Overall, results indicate that CERQ-Ck has similar psychometric properties to the original instrument as well as with adequate reliability and validity to investigate the nine cognitive emotion regulation strategies during late childhood developmental periods. PMID:26925586

Chinese Adaptation and Psychometric Properties of the Child Version of the Cognitive Emotion Regulation Questionnaire.

PubMed

Liu, Wen; Chen, Liang; Blue, Philip R

2016-01-01

This study aimed to validate a Chinese's adaption of the Cognitive Emotion Regulation Questionnaire for children (CERQ-Ck). This self-report instrument evaluates nine cognitive emotion regulation strategies that can be used by children after experiencing a negative life event. The CERQ-Ck was evaluated in a sample of 1403 elementary students between the ages of 9 and 11 by using cluster sampling. All the item-correlation coefficients for CERQ-Ck were above 0.30. The internal consistencies of the nine factors suggested moderate reliability (0.66 to 0.73). Confirmatory factor analysis (CFA) indicated that the current version had the same structure as the original instrument (Tucker-Lewis index = 0.912, comparative fit index = 0.922, root mean square error of approximation = 0.032, standardized root mean square residual = 0.044). A second-order factor and a third-order factor structure were also found. Test-retest correlations (0.53 to 0.70, ps < 0.01) over a period of 1 month, which ranged from acceptable to moderately strong were obtained from a random and stratified subsample of elementary students (N = 76). In addition, we analyzed convergent validity in relation to CERQ-Ck and the Chinese version of the Children's Depression Inventory model dimensions with a subsample of 1083 elementary students. Multiple-group CFA confirmed the measurement invariance for both the male and female groups (ΔCFI < 0.01, ΔRMSEA < 0.015). Overall, results indicate that CERQ-Ck has similar psychometric properties to the original instrument as well as with adequate reliability and validity to investigate the nine cognitive emotion regulation strategies during late childhood developmental periods.

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Random sample consensus combined with partial least squares regression (RANSAC-PLS) for microbial metabolomics data mining and phenotype improvement.

PubMed

Teoh, Shao Thing; Kitamura, Miki; Nakayama, Yasumune; Putri, Sastia; Mukai, Yukio; Fukusaki, Eiichiro

2016-08-01

In recent years, the advent of high-throughput omics technology has made possible a new class of strain engineering approaches, based on identification of possible gene targets for phenotype improvement from omic-level comparison of different strains or growth conditions. Metabolomics, with its focus on the omic level closest to the phenotype, lends itself naturally to this semi-rational methodology. When a quantitative phenotype such as growth rate under stress is considered, regression modeling using multivariate techniques such as partial least squares (PLS) is often used to identify metabolites correlated with the target phenotype. However, linear modeling techniques such as PLS require a consistent metabolite-phenotype trend across the samples, which may not be the case when outliers or multiple conflicting trends are present in the data. To address this, we proposed a data-mining strategy that utilizes random sample consensus (RANSAC) to select subsets of samples with consistent trends for construction of better regression models. By applying a combination of RANSAC and PLS (RANSAC-PLS) to a dataset from a previous study (gas chromatography/mass spectrometry metabolomics data and 1-butanol tolerance of 19 yeast mutant strains), new metabolites were indicated to be correlated with tolerance within certain subsets of the samples. The relevance of these metabolites to 1-butanol tolerance were then validated from single-deletion strains of corresponding metabolic genes. The results showed that RANSAC-PLS is a promising strategy to identify unique metabolites that provide additional hints for phenotype improvement, which could not be detected by traditional PLS modeling using the entire dataset. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Faster diffraction-based overlay measurements with smaller targets using 3D gratings

NASA Astrophysics Data System (ADS)

Li, Jie; Kritsun, Oleg; Liu, Yongdong; Dasari, Prasad; Volkman, Catherine; Hu, Jiangtao

2012-03-01

Diffraction-based overlay (DBO) technologies have been developed to address the overlay metrology challenges for 22nm technology node and beyond. Most DBO technologies require specially designed targets that consist of multiple measurement pads, which consume too much space and increase measurement time. The traditional empirical approach (eDBO) using normal incidence spectroscopic reflectometry (NISR) relies on linear response of the reflectance with respect to overlay displacement within a small range. It offers convenience of quick recipe setup since there is no need to establish a model. However it requires three or four pads per direction (x or y) which adds burden to throughput and target size. Recent advances in modeling capability and computation power enabled mDBO, which allows overlay measurement with reduced number of pads, thus reducing measurement time and DBO target space. In this paper we evaluate the performance of single pad mDBO measurements using two 3D targets that have different grating shapes: squares in boxes and L-shapes in boxes. Good overlay sensitivities are observed for both targets. The correlation to programmed shifts and image-based overlay (IBO) is excellent. Despite the difference in shapes, the mDBO results are comparable for square and L-shape targets. The impact of process variations on overlay measurements is studied using a focus and exposure matrix (FEM) wafer. Although the FEM wafer has larger process variations, the correlation of mDBO results with IBO measurements is as good as the normal process wafer. We demonstrate the feasibility of single pad DBO measurements with faster throughput and smaller target size, which is particularly important in high volume manufacturing environment.

Improvement of correlation-based centroiding methods for point source Shack-Hartmann wavefront sensor

NASA Astrophysics Data System (ADS)

Li, Xuxu; Li, Xinyang; wang, Caixia

2018-03-01

This paper proposes an efficient approach to decrease the computational costs of correlation-based centroiding methods used for point source Shack-Hartmann wavefront sensors. Four typical similarity functions have been compared, i.e. the absolute difference function (ADF), ADF square (ADF2), square difference function (SDF), and cross-correlation function (CCF) using the Gaussian spot model. By combining them with fast search algorithms, such as three-step search (TSS), two-dimensional logarithmic search (TDL), cross search (CS), and orthogonal search (OS), computational costs can be reduced drastically without affecting the accuracy of centroid detection. Specifically, OS reduces calculation consumption by 90%. A comprehensive simulation indicates that CCF exhibits a better performance than other functions under various light-level conditions. Besides, the effectiveness of fast search algorithms has been verified.

System size and energy dependence of jet-induced hadron pair correlation shapes in Cu+Cu and Au+Au collisions at square root sNN=200 and 62.4 GeV.

PubMed

Adare, A; Adler, S S; Afanasiev, S; Aidala, C; Ajitanand, N N; Akiba, Y; Al-Bataineh, H; Alexander, J; Al-Jamel, A; Aoki, K; Aphecetche, L; Armendariz, R; Aronson, S H; Asai, J; Atomssa, E T; Averbeck, R; Awes, T C; Azmoun, B; Babintsev, V; Baksay, G; Baksay, L; Baldisseri, A; Barish, K N; Barnes, P D; Bassalleck, B; Bathe, S; Batsouli, S; Baublis, V; Bauer, F; Bazilevsky, A; Belikov, S; Bennett, R; Berdnikov, Y; Bickley, A A; Bjorndal, M T; Boissevain, J G; Borel, H; Boyle, K; Brooks, M L; Brown, D S; Bruner, N; Bucher, D; Buesching, H; Bumazhnov, V; Bunce, G; Burward-Hoy, J M; Butsyk, S; Camard, X; Campbell, S; Chai, J-S; Chand, P; Chang, B S; Chang, W C; Charvet, J-L; Chernichenko, S; Chiba, J; Chi, C Y; Chiu, M; Choi, I J; Choudhury, R K; Chujo, T; Chung, P; Churyn, A; Cianciolo, V; Cleven, C R; Cobigo, Y; Cole, B A; Comets, M P; Constantin, P; Csanád, M; Csörgo, T; Cussonneau, J P; Dahms, T; Das, K; David, G; Deák, F; Deaton, M B; Dehmelt, K; Delagrange, H; Denisov, A; d'Enterria, D; Deshpande, A; Desmond, E J; Devismes, A; Dietzsch, O; Dion, A; Donadelli, M; Drachenberg, J L; Drapier, O; Drees, A; Dubey, A K; Durum, A; Dutta, D; Dzhordzhadze, V; Efremenko, Y V; Egdemir, J; Ellinghaus, F; Emam, W S; Enokizono, A; En'yo, H; Espagnon, B; Esumi, S; Eyser, K O; Fields, D E; Finck, C; Finger, M; Finger, M; Fleuret, F; Fokin, S L; Forestier, B; Fox, B D; Fraenkel, Z; Frantz, J E; Franz, A; Frawley, A D; Fujiwara, K; Fukao, Y; Fung, S-Y; Fusayasu, T; Gadrat, S; Garishvili, I; Gastineau, F; Germain, M; Glenn, A; Gong, H; Gonin, M; Gosset, J; Goto, Y; Granier de Cassagnac, R; Grau, N; Greene, S V; Grosse Perdekamp, M; Gunji, T; Gustafsson, H-A; Hachiya, T; Hadj Henni, A; Haegemann, C; Haggerty, J S; Hagiwara, M N; Hamagaki, H; Han, R; Hansen, A G; Harada, H; Hartouni, E P; Haruna, K; Harvey, M; Haslum, E; Hasuko, K; Hayano, R; Heffner, M; Hemmick, T K; Hester, T; Heuser, J M; He, X; Hidas, P; Hiejima, H; Hill, J C; Hobbs, R; Hohlmann, M; Holmes, M; Holzmann, W; Homma, K; Hong, B; Hoover, A; Horaguchi, T; Hornback, D; Hur, M G; Ichihara, T; Ikonnikov, V V; Imai, K; Inaba, M; Inoue, Y; Inuzuka, M; Isenhower, D; Isenhower, L; Ishihara, M; Isobe, T; Issah, M; Isupov, A; Jacak, B V; Jia, J; Jin, J; Jinnouchi, O; Johnson, B M; Johnson, S C; Joo, K S; Jouan, D; Kajihara, F; Kametani, S; Kamihara, N; Kamin, J; Kaneta, M; Kang, J H; Kanou, H; Katou, K; Kawabata, T; Kawagishi, T; Kawall, D; Kazantsev, A V; Kelly, S; Khachaturov, B; Khanzadeev, A; Kikuchi, J; Kim, D H; Kim, D J; Kim, E; Kim, G-B; Kim, H J; Kim, Y-S; Kinney, E; Kiss, A; Kistenev, E; Kiyomichi, A; Klay, J; Klein-Boesing, C; Kobayashi, H; Kochenda, L; Kochetkov, V; Kohara, R; Komkov, B; Konno, M; Kotchetkov, D; Kozlov, A; Král, A; Kravitz, A; Kroon, P J; Kubart, J; Kuberg, C H; Kunde, G J; Kurihara, N; Kurita, K; Kweon, M J; Kwon, Y; Kyle, G S; Lacey, R; Lai, Y-S; Lajoie, J G; Lebedev, A; Le Bornec, Y; Leckey, S; Lee, D M; Lee, M K; Lee, T; Leitch, M J; Leite, M A L; Lenzi, B; Lim, H; Liska, T; Litvinenko, A; Liu, M X; Li, X; Li, X H; Love, B; Lynch, D; Maguire, C F; Makdisi, Y I; Malakhov, A; Malik, M D; Manko, V I; Mao, Y; Martinez, G; Masek, L; Masui, H; Matathias, F; Matsumoto, T; McCain, M C; McCumber, M; McGaughey, P L; Miake, Y; Mikes, P; Miki, K; Miller, T E; Milov, A; Mioduszewski, S; Mishra, G C; Mishra, M; Mitchell, J T; Mitrovski, M; Mohanty, A K; Morreale, A; Morrison, D P; Moss, J M; Moukhanova, T V; Mukhopadhyay, D; Muniruzzaman, M; Murata, J; Nagamiya, S; Nagata, Y; Nagle, J L; Naglis, M; Nakagawa, I; Nakamiya, Y; Nakamura, T; Nakano, K; Newby, J; Nguyen, M; Norman, B E; Nyanin, A S; Nystrand, J; O'Brien, E; Oda, S X; Ogilvie, C A; Ohnishi, H; Ojha, I D; Okada, H; Okada, K; Oka, M; Omiwade, O O; Oskarsson, A; Otterlund, I; Ouchida, M; Oyama, K; Ozawa, K; Pak, R; Pal, D; Palounek, A P T; Pantuev, V; Papavassiliou, V; Park, J; Park, W J; Pate, S F; Pei, H; Penev, V; Peng, J-C; Pereira, H; Peresedov, V; Peressounko, D Yu; Pierson, A; Pinkenburg, C; Pisani, R P; Purschke, M L; Purwar, A K; Qualls, J M; Qu, H; Rak, J; Rakotozafindrabe, A; Ravinovich, I; Read, K F; Rembeczki, S; Reuter, M; Reygers, K; Riabov, V; Riabov, Y; Roche, G; Romana, A; Rosati, M; Rosendahl, S S E; Rosnet, P; Rukoyatkin, P; Rykov, V L; Ryu, S S; Sahlmueller, B; Saito, N; Sakaguchi, T; Sakai, S; Sakata, H; Samsonov, V; Sanfratello, L; Santo, R; Sato, H D; Sato, S; Sawada, S; Schutz, Y; Seele, J; Seidl, R; Semenov, V; Seto, R; Sharma, D; Shea, T K; Shein, I; Shevel, A; Shibata, T-A; Shigaki, K; Shimomura, M; Shohjoh, T; Shoji, K; Sickles, A; Silva, C L; Silvermyr, D; Silvestre, C; Sim, K S; Singh, C P; Singh, V; Skutnik, S; Slunecka, M; Smith, W C; Soldatov, A; Soltz, R A; Sondheim, W E; Sorensen, S P; Sourikova, I V; Staley, F; Stankus, P W; Stenlund, E; Stepanov, M; Ster, A; Stoll, S P; Sugitate, T; Suire, C; Sullivan, J P; Sziklai, J; Tabaru, T; Takagi, S; Takagui, E M; Taketani, A; Tanaka, K H; Tanaka, Y; Tanida, K; Tannenbaum, M J; Taranenko, A; Tarján, P; Thomas, T L; Togawa, M; Toia, A; Tojo, J; Tomásek, L; Torii, H; Towell, R S; Tram, V-N; Tserruya, I; Tsuchimoto, Y; Tuli, S K; Tydesjö, H; Tyurin, N; Uam, T J; Vale, C; Valle, H; vanHecke, H W; Velkovska, J; Velkovsky, M; Vertesi, R; Veszprémi, V; Vinogradov, A A; Virius, M; Volkov, M A; Vrba, V; Vznuzdaev, E; Wagner, M; Walker, D; Wang, X R; Watanabe, Y; Wessels, J; White, S N; Willis, N; Winter, D; Wohn, F K; Woody, C L; Wysocki, M; Xie, W; Yamaguchi, Y L; Yanovich, A; Yasin, Z; Ying, J; Yokkaichi, S; Young, G R; Younus, I; Yushmanov, I E; Zajc, W A; Zaudtke, O; Zhang, C; Zhou, S; Zimányi, J; Zolin, L; Zong, X

2007-06-08

We present azimuthal angle correlations of intermediate transverse momentum (1-4 GeV/c) hadrons from dijets in Cu+Cu and Au+Au collisions at square root sNN=62.4 and 200 GeV. The away-side dijet induced azimuthal correlation is broadened, non-Gaussian, and peaked away from Delta phi=pi in central and semicentral collisions in all the systems. The broadening and peak location are found to depend upon the number of participants in the collision, but not on the collision energy or beam nuclei. These results are consistent with sound or shock wave models, but pose challenges to Cherenkov gluon radiation models.

Exploring the effects of coexisting amyloid in subcortical vascular cognitive impairment.

PubMed

Dao, Elizabeth; Hsiung, Ging-Yuek Robin; Sossi, Vesna; Jacova, Claudia; Tam, Roger; Dinelle, Katie; Best, John R; Liu-Ambrose, Teresa

2015-10-12

Mixed pathology, particularly Alzheimer's disease with cerebrovascular lesions, is reported as the second most common cause of dementia. Research on mixed dementia typically includes people with a primary AD diagnosis and hence, little is known about the effects of co-existing amyloid pathology in people with vascular cognitive impairment (VCI). The purpose of this study was to understand whether individual differences in amyloid pathology might explain variations in cognitive impairment among individuals with clinical subcortical VCI (SVCI). Twenty-two participants with SVCI completed an (11)C Pittsburgh compound B (PIB) position emission tomography (PET) scan to quantify global amyloid deposition. Cognitive function was measured using: 1) MOCA; 2) ADAS-Cog; 3) EXIT-25; and 4) specific executive processes including a) Digits Forward and Backwards Test, b) Stroop-Colour Word Test, and c) Trail Making Test. To assess the effect of amyloid deposition on cognitive function we conducted Pearson bivariate correlations to determine which cognitive measures to include in our regression models. Cognitive variables that were significantly correlated with PIB retention values were entered in a hierarchical multiple linear regression analysis to determine the unique effect of amyloid on cognitive function. We controlled for age, education, and ApoE ε4 status. Bivariate correlation results showed that PIB binding was significantly correlated with ADAS-Cog (p < 0.01) and MOCA (p < 0.01); increased PIB binding was associated with worse cognitive function on both cognitive measures. PIB binding was not significantly correlated with the EXIT-25 or with specific executive processes (p > 0.05). Regression analyses controlling for age, education, and ApoE ε4 status indicated an independent association between PIB retention and the ADAS-Cog (adjusted R-square change of 15.0%, Sig F Change = 0.03). PIB retention was also independently associated with MOCA scores (adjusted R-Square Change of 27.0%, Sig F Change = 0.02). We found that increased global amyloid deposition was significantly associated with greater memory and executive dysfunctions as measured by the ADAS-Cog and MOCA. Our findings point to the important role of co-existing amyloid deposition for cognitive function in those with a primary SVCI diagnosis. As such, therapeutic approaches targeting SVCI must consider the potential role of amyloid for the optimal care of those with mixed dementia. NCT01027858.

Feasibility of the simultaneous determination of polycyclic aromatic hydrocarbons based on two-dimensional fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Renjie; Dong, Guimei; Sun, Xueshan; Yang, Yanrong; Yu, Yaping; Liu, Haixue; Zhang, Weiyu

2018-02-01

A new approach for quantitative determination of polycyclic aromatic hydrocarbons (PAHs) in environment was proposed based on two-dimensional (2D) fluorescence correlation spectroscopy in conjunction with multivariate method. 40 mixture solutions of anthracene and pyrene were prepared in the laboratory. Excitation-emission matrix (EEM) fluorescence spectra of all samples were collected. And 2D fluorescence correlation spectra were calculated under the excitation perturbation. The N-way partial least squares (N-PLS) models were developed based on 2D fluorescence correlation spectra, showing a root mean square error of calibration (RMSEC) of 3.50 μg L- 1 and root mean square error of prediction (RMSEP) of 4.42 μg L- 1 for anthracene and of 3.61 μg L- 1 and 4.29 μg L- 1 for pyrene, respectively. Also, the N-PLS models were developed for quantitative analysis of anthracene and pyrene using EEM fluorescence spectra. The RMSEC and RMSEP were 3.97 μg L- 1 and 4.63 μg L- 1 for anthracene, 4.46 μg L- 1 and 4.52 μg L- 1 for pyrene, respectively. It was found that the N-PLS model using 2D fluorescence correlation spectra could provide better results comparing with EEM fluorescence spectra because of its low RMSEC and RMSEP. The methodology proposed has the potential to be an alternative method for detection of PAHs in environment.

On roots and squares - estimation, intuition and creativity

NASA Astrophysics Data System (ADS)

Patkin, Dorit; Gazit, Avikam

2013-12-01

The paper presents findings of a small scale study of a few items related to problem solving with squares and roots, for different teacher groups (pre-service and in-service mathematics teachers: elementary and junior high school). The research participants were asked to explain what would be the units digit of a natural number to be squared in order to obtain a certain units digit as a result. They were also asked to formulate a rule - an algorithm for calculating the square of a 2-digit number which is a multiple of 5. Based on this knowledge and estimation capability, they were required to find, without using calculators, the square roots of given natural numbers. The findings show that most of the participants had only partial intuition regarding the units' digit of a number which is squared when the units' digit of the square is known. At the same time, the participants manifested some evidence of creativity and flow of ideas in identifying the rule for calculating the square of a natural number whose units digit is 5. However, when asked to identify, by means of estimation and based on knowledge from previous items, the square roots of three natural numbers, only few of them managed to find the three roots by estimation.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

Endodontic flare-ups: comparison of incidence between single and multiple visits procedures in patients attending a Nigerian teaching hospital.

PubMed

Oginni, Ao; Udoye, C I

2004-12-01

The present study was performed to compare the incidence of endodontic flare ups in single with multiple visits treatment procedures, to establish the relationship between pre-operative and post obturation pain in patients attending for endodontic therapy in a Nigerian teaching Hospital. Patients were randomly assigned to either single visit or multiple visits group. Data collected at root canal treatment appointment and recall visits (1st, 7th and 30th day post obturation) include pulp vitality status, the presence or absence of pre-operative pain, presence and degree of post obturation pain. Presence of endodontic flare-ups (defined as either patient's report of pain not controlled with over the counter medication and or increasing swelling). The compiled data were analyzed using chi-square where applicable. P level < 0.05 was taken as significant. Ten endodontic flare-ups (8.1 %) were recorded in the multiple visits group compared to 19 (18,3%) flare-ups for the single visit group, P = 0.02. For both single and multiple visits procedures, there were statistically significant correlations between pre operative and post obturation pain (P = 0.002 and P = 0.0004 respectively). Teeth with vital pulps reported the lowest frequency of post obturation pain (48.8%), while those with non vital pulps were found to have the highest frequency oh post obturation pain (50,3%), P = 0.9. Although the present study reported higher incidences for post obturation pain and flare-ups following the single visit procedures, single visit endodontic therapy has been shown to be a safe and effective alternative to multiple visits treatment.

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

Square2 - A Web Application for Data Monitoring in Epidemiological and Clinical Studies

PubMed

Schmidt, Carsten Oliver; Krabbe, Christine; Schössow, Janka; Albers, Martin; Radke, Dörte; Henke, Jörg

2017-01-01

Valid scientific inferences from epidemiological and clinical studies require high data quality. Data generating departments therefore aim to detect data irregularities as early as possible in order to guide quality management processes. In addition, after the completion of data collections the obtained data quality must be evaluated. This can be challenging in complex studies due to a wide scope of examinations, numerous study variables, multiple examiners, devices, and examination centers. This paper describes a Java EE web application used to monitor and evaluate data quality in institutions with complex and multiple studies, named Square 2 . It uses the Java libraries Apache MyFaces 2, extended by BootsFaces for layout and style. RServe and REngine manage calls to R server processes. All study data and metadata are stored in PostgreSQL. R is the statistics backend and LaTeX is used for the generation of print ready PDF reports. A GUI manages the entire workflow. Square 2 covers all steps in the data monitoring workflow, including the setup of studies and their structure, the handling of metadata for data monitoring purposes, selection of variables, upload of data, statistical analyses, and the generation as well as inspection of quality reports. To take into account data protection issues, Square 2 comprises an extensive user rights and roles concept.

A feasibility study for long-path multiple detection using a neural network

NASA Technical Reports Server (NTRS)

Feuerbacher, G. A.; Moebes, T. A.

1994-01-01

Least-squares inverse filters have found widespread use in the deconvolution of seismograms and the removal of multiples. The use of least-squares prediction filters with prediction distances greater than unity leads to the method of predictive deconvolution which can be used for the removal of long path multiples. The predictive technique allows one to control the length of the desired output wavelet by control of the predictive distance, and hence to specify the desired degree of resolution. Events which are periodic within given repetition ranges can be attenuated selectively. The method is thus effective in the suppression of rather complex reverberation patterns. A back propagation(BP) neural network is constructed to perform the detection of first arrivals of the multiples and therefore aid in the more accurate determination of the predictive distance of the multiples. The neural detector is applied to synthetic reflection coefficients and synthetic seismic traces. The processing results show that the neural detector is accurate and should lead to an automated fast method for determining predictive distances across vast amounts of data such as seismic field records. The neural network system used in this study was the NASA Software Technology Branch's NETS system.

Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics

NASA Astrophysics Data System (ADS)

Su, Qi; Li, Aming; Wang, Long

2017-02-01

Spatial reciprocity is generally regarded as a positive rule facilitating the evolution of cooperation. However, a few recent studies show that, in the snowdrift game, spatial structure still could be detrimental to cooperation. Here we propose a model of multiple interactive dynamics, where each individual can cooperate and defect simultaneously against different neighbors. We realize individuals' multiple interactions simply by endowing them with strategies relevant to probabilities, and every one decides to cooperate or defect with a probability. With multiple interactive dynamics, the cooperation level in square lattices is higher than that in the well-mixed case for a wide range of cost-to-benefit ratio r, implying that spatial structure favors cooperative behavior in the snowdrift game. Moreover, in square lattices, the most favorable strategy follows a simple relation of r, which confers theoretically the average evolutionary frequency of cooperative behavior. We further extend our study to various homogeneous and heterogeneous networks, which demonstrates the robustness of our results. Here multiple interactive dynamics stabilizes the positive role of spatial structure on the evolution of cooperation and individuals' distinct reactions to different neighbors can be a new line in understanding the emergence of cooperation.

High Predictive Skill of Global Surface Temperature a Year Ahead

NASA Astrophysics Data System (ADS)

Folland, C. K.; Colman, A.; Kennedy, J. J.; Knight, J.; Parker, D. E.; Stott, P.; Smith, D. M.; Boucher, O.

2011-12-01

We discuss the high skill of real-time forecasts of global surface temperature a year ahead issued by the UK Met Office, and their scientific background. Although this is a forecasting and not a formal attribution study, we show that the main instrumental global annual surface temperature data sets since 1891 are structured consistently with a set of five physical forcing factors except during and just after the second World War. Reconstructions use a multiple application of cross validated linear regression to minimise artificial skill allowing time-varying uncertainties in the contribution of each forcing factor to global temperature to be assessed. Mean cross validated reconstructions for the data sets have total correlations in the range 0.93-0.95,interannual correlations in the range 0.72-0.75 and root mean squared errors near 0.06oC, consistent with observational uncertainties.Three transient runs of the HadCM3 coupled model for 1888-2002 demonstrate quite similar reconstruction skill from similar forcing factors defined appropriately for the model, showing that skilful use of our technique is not confined to observations. The observed reconstructions show that the Atlantic Multidecadal Oscillation (AMO) likely contributed to the re-commencement of global warming between 1976 and 2010 and to global cooling observed immediately beforehand in 1965-1976. The slowing of global warming in the last decade is likely to be largely due to a phase-delayed response to the downturn in the solar cycle since 2001-2, with no net ENSO contribution. The much reduced trend in 2001-10 is similar in size to other weak decadal temperature trends observed since global warming resumed in the 1970s. The causes of variations in decadal trends can be mostly explained by variations in the strength of the forcing factors. Eleven real-time forecasts of global mean surface temperature for the year ahead for 2000-2010, based on broadly similar methods, provide an independent test of the ideas of this study. They had the high correlation and root mean square error skill levels compared to observations of 0.74 and 0.07oC respectively. Pseudo-forecasts for the same period reconstructed from somewhat improved forcing data used for this study had the slightly better correlation of 0.80 and root mean squared error of 0.05oC. Finally we compare the statistical forecasts with dynamical hindcasts and forecasts of global surface temperature a year ahead made by the Met Office DePreSys coupled model. The statistical and dynamical forecasts of global surface temperature for 2011 will be compared with preliminary verification data.

Pseudobulbar Affect Correlates With Mood Symptoms in Parkinsonian Disorders but Not Amyotrophic Lateral Sclerosis.

PubMed

Patel, Neepa; Combs, Hannah; York, Michele; Phan, Cecile; Jimenez-Shahed, Joohi

2018-03-05

Pseudobulbar affect (PBA) is a syndrome of affective disturbance associated with inappropriate laughter and crying, independent of mood. PBA is common in amyotrophic lateral sclerosis (ALS) and increasingly recognized in Parkinson's disease (PD) and atypical parkinsonism (aP). Correlates of PBA have not been systematically studied. The purpose of this study was to determine whether cognitive and psychiatric comorbidities correlated with patient-reported symptoms of PBA by using the Center for Neurological Study-Lability Scale among patients with ALS, PD, and aP. A total of 108 patients (PD, N=53; aP, N=29; ALS, N=26) completed a cognitive screener and self-reported measures of lability, depression, anxiety, apathy, and quality of life. Statistical analyses included one- and two-way analyses of covariance to evaluate group differences, Pearson's correlations to determine relationships between PBA symptoms and comorbidities, multiple regression for predicting PBA symptom severity in clinical correlates, and chi-square t tests for predicting demographic variables. PBA symptom severity did not vary between the three groups. Younger age and worse anxiety correlated with PBA symptom severity in all three groups, whereas depression and poor mental health/quality of life only correlated with PBA symptom severity in the PD and aP groups. PD and aP patients may be more likely to benefit from treatment with antidepressants. Increased PBA symptoms were associated with declines in cognitive functioning in the aP group, but sufficient numbers of PD and ALS patients with cognitive dysfunction may not have been recruited. The results suggest the possibility of an alternate pathophysiologic mechanism for PBA, which may vary between neurological disorders and disease progression. Mood and cognition are of particular relevance and should be evaluated when symptoms of PBA are suspected.

Cross-correlation least-squares reverse time migration in the pseudo-time domain

NASA Astrophysics Data System (ADS)

Li, Qingyang; Huang, Jianping; Li, Zhenchun

2017-08-01

The least-squares reverse time migration (LSRTM) method with higher image resolution and amplitude is becoming increasingly popular. However, the LSRTM is not widely used in field land data processing because of its sensitivity to the initial migration velocity model, large computational cost and mismatch of amplitudes between the synthetic and observed data. To overcome the shortcomings of the conventional LSRTM, we propose a cross-correlation least-squares reverse time migration algorithm in pseudo-time domain (PTCLSRTM). Our algorithm not only reduces the depth/velocity ambiguities, but also reduces the effect of velocity error on the imaging results. It relieves the accuracy requirements on the migration velocity model of least-squares migration (LSM). The pseudo-time domain algorithm eliminates the irregular wavelength sampling in the vertical direction, thus it can reduce the vertical grid points and memory requirements used during computation, which makes our method more computationally efficient than the standard implementation. Besides, for field data applications, matching the recorded amplitudes is a very difficult task because of the viscoelastic nature of the Earth and inaccuracies in the estimation of the source wavelet. To relax the requirement for strong amplitude matching of LSM, we extend the normalized cross-correlation objective function to the pseudo-time domain. Our method is only sensitive to the similarity between the predicted and the observed data. Numerical tests on synthetic and land field data confirm the effectiveness of our method and its adaptability for complex models.

A Comparison of Latent Growth Models for Constructs Measured by Multiple Items

ERIC Educational Resources Information Center

Leite, Walter L.

2007-01-01

Univariate latent growth modeling (LGM) of composites of multiple items (e.g., item means or sums) has been frequently used to analyze the growth of latent constructs. This study evaluated whether LGM of composites yields unbiased parameter estimates, standard errors, chi-square statistics, and adequate fit indexes. Furthermore, LGM was compared…

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Normalization Ridge Regression in Practice II: The Estimation of Multiple Feedback Linkages.

ERIC Educational Resources Information Center

Bulcock, J. W.

The use of the two-stage least squares (2 SLS) procedure for estimating nonrecursive social science models is often impractical when multiple feedback linkages are required. This is because 2 SLS is extremely sensitive to multicollinearity. The standard statistical solution to the multicollinearity problem is a biased, variance reduced procedure…

Effects of Verbal and Written Performance Feedback on Treatment Adherence: Practical Application of Two Delivery Formats

ERIC Educational Resources Information Center

Kaufman, Dahlia; Codding, Robin S.; Markus, Keith A.; Tryon, Georgiana Shick; Kyse, Eden Nagler

2013-01-01

Verbal and written performance feedback for improving preschool and kindergarten teachers' treatment integrity of behavior plans was compared using a combined multiple-baseline and multiple-treatment design across teacher-student dyads with order counterbalanced as within-series conditions. Supplemental generalized least square regression analyses…

"You Have to Count the Squares": Applying Knowledge in Pieces to Learning Rectangular Area

ERIC Educational Resources Information Center

Izsak, Andrew

2005-01-01

This article extends and strengthens the knowledge in pieces perspective (diSessa, 1988, 1993) by applying core components to analyze how 5th-grade students with computational knowledge of whole-number multiplication and connections between multiplication and discrete arrays constructed understandings of area and ways of using representations to…

Combination of multiple model population analysis and mid-infrared technology for the estimation of copper content in Tegillarca granosa

NASA Astrophysics Data System (ADS)

Hu, Meng-Han; Chen, Xiao-Jing; Ye, Peng-Chao; Chen, Xi; Shi, Yi-Jian; Zhai, Guang-Tao; Yang, Xiao-Kang

2016-11-01

The aim of this study was to use mid-infrared spectroscopy coupled with multiple model population analysis based on Monte Carlo-uninformative variable elimination for rapidly estimating the copper content of Tegillarca granosa. Copper-specific wavelengths were first extracted from the whole spectra, and subsequently, a least square-support vector machine was used to develop the prediction models. Compared with the prediction model based on full wavelengths, models that used 100 multiple MC-UVE selected wavelengths without and with bin operation showed comparable performances with Rp (root mean square error of Prediction) of 0.97 (14.60 mg/kg) and 0.94 (20.85 mg/kg) versus 0.96 (17.27 mg/kg), as well as ratio of percent deviation (number of wavelength) of 2.77 (407) and 1.84 (45) versus 2.32 (1762). The obtained results demonstrated that the mid-infrared technique could be used for estimating copper content in T. granosa. In addition, the proposed multiple model population analysis can eliminate uninformative, weakly informative and interfering wavelengths effectively, that substantially reduced the model complexity and computation time.

[Application of genetic algorithm in blending technology for extractions of Cortex Fraxini].

PubMed

Yang, Ming; Zhou, Yinmin; Chen, Jialei; Yu, Minying; Shi, Xiufeng; Gu, Xijun

2009-10-01

To explore the feasibility of genetic algorithm (GA) on multiple objective blending technology for extractions of Cortex Fraxini. According to that the optimization objective was the combination of fingerprint similarity and the root-mean-square error of multiple key constituents, a new multiple objective optimization model of 10 batches extractions of Cortex Fraxini was built. The blending coefficient was obtained by genetic algorithm. The quality of 10 batches extractions of Cortex Fraxini that after blending was evaluated with the finger print similarity and root-mean-square error as indexes. The quality of 10 batches extractions of Cortex Fraxini that after blending was well improved. Comparing with the fingerprint of the control sample, the similarity was up, but the degree of variation is down. The relative deviation of the key constituents was less than 10%. It is proved that genetic algorithm works well on multiple objective blending technology for extractions of Cortex Fraxini. This method can be a reference to control the quality of extractions of Cortex Fraxini. Genetic algorithm in blending technology for extractions of Chinese medicines is advisable.

Stencils and problem partitionings: Their influence on the performance of multiple processor systems

NASA Technical Reports Server (NTRS)

Reed, D. A.; Adams, L. M.; Patrick, M. L.

1986-01-01

Given a discretization stencil, partitioning the problem domain is an important first step for the efficient solution of partial differential equations on multiple processor systems. Partitions are derived that minimize interprocessor communication when the number of processors is known a priori and each domain partition is assigned to a different processor. This partitioning technique uses the stencil structure to select appropriate partition shapes. For square problem domains, it is shown that non-standard partitions (e.g., hexagons) are frequently preferable to the standard square partitions for a variety of commonly used stencils. This investigation is concluded with a formalization of the relationship between partition shape, stencil structure, and architecture, allowing selection of optimal partitions for a variety of parallel systems.

A simple test of association for contingency tables with multiple column responses.

PubMed

Decady, Y J; Thomas, D R

2000-09-01

Loughin and Scherer (1998, Biometrics 54, 630-637) investigated tests of association in two-way tables when one of the categorical variables allows for multiple-category responses from individual respondents. Standard chi-squared tests are invalid in this case, and they developed a bootstrap test procedure that provides good control of test levels under the null hypothesis. This procedure and some others that have been proposed are computationally involved and are based on techniques that are relatively unfamiliar to many practitioners. In this paper, the methods introduced by Rao and Scott (1981, Journal of the American Statistical Association 76, 221-230) for analyzing complex survey data are used to develop a simple test based on a corrected chi-squared statistic.

Meta-Analytic Methods of Pooling Correlation Matrices for Structural Equation Modeling under Different Patterns of Missing Data

ERIC Educational Resources Information Center

Furlow, Carolyn F.; Beretvas, S. Natasha

2005-01-01

Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…

Correlates of Alaska Native Fatal and Nonfatal Suicidal Behaviors 1990-2001

ERIC Educational Resources Information Center

Wexler, Lisa; Hill, Ryan; Bertone-Johnson, Elizabeth; Fenaughty, Andrea

2008-01-01

Factors correlated with suicidal behavior in a predominately Alaska Native region of Alaska are described, and the correlates relating to fatal and nonfatal suicide behaviors in this indigenous population are distinguished. Suicide data from the region (1990-2001) were aggregated and compared to 2000 U.S. Census Data using chi-squared tests.…

Process for obtaining multiple sheet resistances for thin film hybrid microcircuit resistors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norwood, D P

1989-01-31

A standard thin film circuit containing Ta/sub 2/N (100 ohms/square) resistors is fabricated by depositing on a dielectric substrate successive layers of Ta/sub 2/N, Ti and Pd, with a gold layer to provide conductors. The addition of a few simple photoprocessing steps to the standard TFN (thin film network) manufacturing process enables the formation of Ta/sub 2/N + Ti (10 ohms/square) and Ta/sub 2/N + Ti + Pd (1 ohm/square) resistors in the same otherwise standard thin film circuit structure. All three types of resistors are temperature-stable and laser-trimmable for precise definition of resistance values.

Flight Test of Orthogonal Square Wave Inputs for Hybrid-Wing-Body Parameter Estimation

NASA Technical Reports Server (NTRS)

Taylor, Brian R.; Ratnayake, Nalin A.

2011-01-01

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will use distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. The research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique in order to determine individual control surface effectiveness. This technique was validated through flight-testing an 8.5-percent-scale hybrid-wing-body aircraft demonstrator at the NASA Dryden Flight Research Center (Edwards, California). An input design technique that uses mutually orthogonal square wave inputs for de-correlation of control surfaces is proposed. Flight-test results are compared with prior flight-test results for a different maneuver style.

Empirical evaluation of the inter-relationship of articular elements involved in the pathoanatomy of knee osteoarthritis using magnetic resonance imaging.

PubMed

Meredith, Dennis S; Losina, Elena; Neumann, Gesa; Yoshioka, Hiroshi; Lang, Philipp K; Katz, Jeffrey N

2009-10-29

In this cross-sectional study, we conducted a comprehensive assessment of all articular elements that could be measured using knee MRI. We assessed the association of pathological change in multiple articular structures involved in the pathoanatomy of osteoarthritis. Knee MRI scans from patients over 45 years old were assessed using a semi-quantitative knee MRI assessment form. The form included six distinct elements: cartilage, bone marrow lesions, osteophytes, subchondral sclerosis, joint effusion and synovitis. Each type of pathology was graded using an ordinal scale with a value of zero indicating no pathology and higher values indicating increasingly severe levels of pathology. The principal dependent variable for comparison was the mean cartilage disease score (CDS), which captured the aggregate extent of involvement of articular cartilage. The distribution of CDS was compared to the individual and cumulative distributions of each articular element using the Chi-squared test. The correlations between pathological change in the various articular structures were assessed in a Spearman correlation table. Data from 140 patients were available for review. The cohort had a median age of 61 years (range 45-89) and was 61% female. The cohort included a wide spectrum of OA severity. Our analysis showed a statistically significant trend towards pathological change involving more articular elements as CDS worsened (p-value for trend < 0.0001). Comparison of CDS to change in the severity of pathology of individual articular elements showed statistically significant trends towards more severe pathology as CDS worsened for osteophytes (p-value for trend < 0.0001), bone marrow lesions (p = 0.0003), and subchondral sclerosis (p = 0.009), but not joint effusion or synovitis. There was a moderate correlation between cartilage damage, osteophytes and BMLs as well as a moderate correlation between joint effusion and synovitis. However, cartilage damage and osteophytes were only weakly associated with synovitis or joint effusion. Our results support an inter-relationship of multiple articular elements in the pathoanatomy of knee OA. Prospective studies of OA pathogenesis in humans are needed to correlate these findings to clinically relevant outcomes such as pain and function.

The use of least squares methods in functional optimization of energy use prediction models

NASA Astrophysics Data System (ADS)

Bourisli, Raed I.; Al-Shammeri, Basma S.; AlAnzi, Adnan A.

2012-06-01

The least squares method (LSM) is used to optimize the coefficients of a closed-form correlation that predicts the annual energy use of buildings based on key envelope design and thermal parameters. Specifically, annual energy use is related to a number parameters like the overall heat transfer coefficients of the wall, roof and glazing, glazing percentage, and building surface area. The building used as a case study is a previously energy-audited mosque in a suburb of Kuwait City, Kuwait. Energy audit results are used to fine-tune the base case mosque model in the VisualDOE{trade mark, serif} software. Subsequently, 1625 different cases of mosques with varying parameters were developed and simulated in order to provide the training data sets for the LSM optimizer. Coefficients of the proposed correlation are then optimized using multivariate least squares analysis. The objective is to minimize the difference between the correlation-predicted results and the VisualDOE-simulation results. It was found that the resulting correlation is able to come up with coefficients for the proposed correlation that reduce the difference between the simulated and predicted results to about 0.81%. In terms of the effects of the various parameters, the newly-defined weighted surface area parameter was found to have the greatest effect on the normalized annual energy use. Insulating the roofs and walls also had a major effect on the building energy use. The proposed correlation and methodology can be used during preliminary design stages to inexpensively assess the impacts of various design variables on the expected energy use. On the other hand, the method can also be used by municipality officials and planners as a tool for recommending energy conservation measures and fine-tuning energy codes.

Multiple soliton production and the Korteweg-de Vries equation.

NASA Technical Reports Server (NTRS)

Hershkowitz, N.; Romesser, T.; Montgomery, D.

1972-01-01

Compressive square-wave pulses are launched in a double-plasma device. Their evolution is interpreted according to the Korteweg-de Vries description of Washimi and Taniuti. Square-wave pulses are an excitation for which an explicit solution of the Schrodinger equation permits an analytical prediction of the number and amplitude of emergent solitons. Bursts of energetic particles (pseudowaves) appear above excitation voltages greater than an electron thermal energy, and may be mistaken for solitons.

Socio-demographic correlates of breast-feeding in urban slums of Chandigarh.

PubMed

Kumar, Dinesh; Agarwal, Neeraj; Swami, H M

2006-11-01

Whether socio-demographic factors are associated with initiation of breast-feeding in urban slums of Chandigarh. (1) To study the prevailing breast-feeding practices adopted by mothers, (2) To study the socio-demographic factors associated with initiation of breast-feeding. Cross-sectional. Mothers of infants willing to participate in the study in the selected area. A total of 270 respondents. Social and demographic characteristics like age, socioeconomic status, educational level, birth interval, parity, gender preference, natal care practices, etc.; and variables related to various aspects of breast-feeding practices like prelacteal feed, initiation of feeding, colostrum feeding, reasons of discarding colostrum, etc. Chi-square test and odd ratios along with their respective 95% confidence intervals, multiple logistic regression analysis. Out of all 270 respondents, 159 (58.9%) initiated breast-feeding within 6 h of birth, only 43 (15.9%) discarded colostrum and 108 (40.0%) mothers gave prelacteal feed. Illiterate/just literate mothers who delivered at home were found at significantly higher risk of delay in initiation of breast-feeding on the basis of multiple logistic regression analysis. Promotion of institutional deliveries and imparting health education to mothers for protecting and promoting optimal breast-feeding practices are suggested.

Neutrophil to lymphocyte ratio as the main predictor of peripheral artery disease in regular hemodialysis patients

NASA Astrophysics Data System (ADS)

Siregar, R. H.; Muzasti, R. A.

2018-03-01

Cardiovascular disease is the most inducer of morbidity and mortality of chronic kidney disease (CKD) patients who have undergone dialysis. Today, neutrophil to lymphocyte ratio (NLR) is considered an indicator of the severity and extent of systemic inflammation and atherosclerosis in patients with renal and cardiovascular disorders. To examine the relationship between NLR with PAD in regular hemodialysis patients, a cross-sectional study, Ankle- Brachial Index (ABI) measurement and peripheral blood examination was on 72 regular hemodialysis patients ≥6 months. The ABI value ≤0.9 is considered PAD. NLR≥ 3.5 is considered abnormal based on some pre-existing research. Prevalence of PAD is 29.16%. Chi- square test showed significant correlation between NLR with PAD (p = 0.0001), multiplication of Calcium and Phosphorus (p = 0.0001), and type 2 Diabetes Mellitus (T2DM) (p = 0.039), multivariate analysis showed that NLR was an independent predictor for PAD in regular hemodialysis patients (RR = 2.271 p = 0.027). In conclusion, NLR, a new inflammatory marker of peripheral blood examination may serve as a marker of PAD in a regular hemodialysis patient, in addition to the multiplication of Calcium and Phosphorus as well as T2DM.

PER3 VNTR polymorphism in Multiple Sclerosis: A new insight to impact of sleep disturbances in MS.

PubMed

Golalipour, Masoud; Maleki, Zahra; Farazmandfar, Touraj; Shahbazi, Majid

2017-10-01

Multiple Sclerosis (MS) is a degenerative disease of central nervous system caused by an immune response against the myelin. About half of MS patients suffers from sleep disturbances. The circadian clock genes such as PER3 controls circadian rhythm and sleep. Due to the role of PER3 in sleep disturbances and regulation of immune response, it is possible that PER3 dysregulation increase risk of MS disease. Study groups included 160 MS patients and 160 healthy volunteers. PER3 VNTR polymorphism was evaluated by PCR method. The genotypic and allelic distribution analyzed by chi square test. There was a significant association between genotype PER3 4/4 , and 4-repeat allele with MS disease (p = 0.014 and p < 0.001 respectively). The association analysis of PER3 VNTR polymorphism with gender status among MS group, and MS onset showed that there was a significant correlation between PER3 4/4 genotype with female gender and early onset of MS disease (p = 0.033 and p = 0.028 respectively). Our data suggest that, PER3 4/4 genotype may accelerate the course of disease in MS susceptible individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

imDEV: a graphical user interface to R multivariate analysis tools in Microsoft Excel.

PubMed

Grapov, Dmitry; Newman, John W

2012-09-01

Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R's multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010).

The relationship between foot pain, anthropometric variables and footwear among older people.

PubMed

Paiva de Castro, Alessandra; Rebelatto, José Rubens; Aurichio, Thaís Rabiatti

2010-01-01

To verify the prevalence of pain among older people when wearing shoes, and the relationships between foot pain, high-heeled shoes and anthropometric variables. Both feet of 227 older women and 172 older men were evaluated with respect to anthropometric variables, arch index and foot posture index. The participants were also asked about the presence of foot pain while wearing high-heeled shoes. The data were analyzed using the Chi-square test, Pearson's correlation, MANOVA, multiple regression analysis, t test, and analysis of probability. The prevalence of foot pain when wearing shoes was high and was associated with the female gender, however wearing high-heeled shoes was not associated with pain. The women with foot pain presented larger values for the circumferences of the metatarsal heads and the instep (after normalization with the foot length) than those without pain. The men with pain did not present different measurements from those without pain.

The prevalence of binge eating disorder and its relationship to work and classroom productivity and activity impairment.

PubMed

Filipova, Anna A; Stoffel, Cheri L

2016-07-01

The study aimed to determine the prevalence of binge eating disorder on university campus, its associations with health risk factors, and its associations with work and classroom productivity and activity impairment, adjusted for health risk factors. The study was conducted at a public midwestern university in the United States and involved 1,165 students. Data were collected online, using preestablished instruments. Descriptive, chi-square, correlation, and robust multiple regression tests were used. About 7.8% of the participants were assessed as having binge eating disorder. Binge eating disorder was more common among obese students than nonobese students. Associations were found between moderate binge eating disorder and classroom productivity and daily activity impairment; however, sleep duration and physical activity were the strongest predictors. University students are at risk of binge eating disorder. Interventions with this population should include education, screening, and clinical consultation when warranted.

Quantitative prediction of solvation free energy in octanol of organic compounds.

PubMed

Delgado, Eduardo J; Jaña, Gonzalo A

2009-03-01

The free energy of solvation, DeltaGS0, in octanol of organic compounds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a DeltaGS0 range from about -50 to 0 kJ.mol(-1). The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ.mol(-1), just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set.

Quantitative Prediction of Solvation Free Energy in Octanol of Organic Compounds

PubMed Central

Delgado, Eduardo J.; Jaña, Gonzalo A.

2009-01-01

The free energy of solvation, ΔGS0, in octanol of organic compunds is quantitatively predicted from the molecular structure. The model, involving only three molecular descriptors, is obtained by multiple linear regression analysis from a data set of 147 compounds containing diverse organic functions, namely, halogenated and non-halogenated alkanes, alkenes, alkynes, aromatics, alcohols, aldehydes, ketones, amines, ethers and esters; covering a ΔGS0 range from about −50 to 0 kJ·mol−1. The model predicts the free energy of solvation with a squared correlation coefficient of 0.93 and a standard deviation, 2.4 kJ·mol−1, just marginally larger than the generally accepted value of experimental uncertainty. The involved molecular descriptors have definite physical meaning corresponding to the different intermolecular interactions occurring in the bulk liquid phase. The model is validated with an external set of 36 compounds not included in the training set. PMID:19399236

Correlation and Stacking of Relative Paleointensity and Oxygen Isotope Data

NASA Astrophysics Data System (ADS)

Lurcock, P. C.; Channell, J. E.; Lee, D.

2012-12-01

The transformation of a depth-series into a time-series is routinely implemented in the geological sciences. This transformation often involves correlation of a depth-series to an astronomically calibrated time-series. Eyeball tie-points with linear interpolation are still regularly used, although these have the disadvantages of being non-repeatable and not based on firm correlation criteria. Two automated correlation methods are compared: the simulated annealing algorithm (Huybers and Wunsch, 2004) and the Match protocol (Lisiecki and Lisiecki, 2002). Simulated annealing seeks to minimize energy (cross-correlation) as "temperature" is slowly decreased. The Match protocol divides records into intervals, applies penalty functions that constrain accumulation rates, and minimizes the sum of the squares of the differences between two series while maintaining the data sequence in each series. Paired relative paleointensity (RPI) and oxygen isotope records, such as those from IODP Site U1308 and/or reference stacks such as LR04 and PISO, are warped using known warping functions, and then the un-warped and warped time-series are correlated to evaluate the efficiency of the correlation methods. Correlations are performed in tandem to simultaneously optimize RPI and oxygen isotope data. Noise spectra are introduced at differing levels to determine correlation efficiency as noise levels change. A third potential method, known as dynamic time warping, involves minimizing the sum of distances between correlated point pairs across the whole series. A "cost matrix" between the two series is analyzed to find a least-cost path through the matrix. This least-cost path is used to nonlinearly map the time/depth of one record onto the depth/time of another. Dynamic time warping can be expanded to more than two dimensions and used to stack multiple time-series. This procedure can improve on arithmetic stacks, which often lose coherent high-frequency content during the stacking process.

Sound field simulation and acoustic animation in urban squares

NASA Astrophysics Data System (ADS)

Kang, Jian; Meng, Yan

2005-04-01

Urban squares are important components of cities, and the acoustic environment is important for their usability. While models and formulae for predicting the sound field in urban squares are important for their soundscape design and improvement, acoustic animation tools would be of great importance for designers as well as for public participation process, given that below a certain sound level, the soundscape evaluation depends mainly on the type of sounds rather than the loudness. This paper first briefly introduces acoustic simulation models developed for urban squares, as well as empirical formulae derived from a series of simulation. It then presents an acoustic animation tool currently being developed. In urban squares there are multiple dynamic sound sources, so that the computation time becomes a main concern. Nevertheless, the requirements for acoustic animation in urban squares are relatively low compared to auditoria. As a result, it is important to simplify the simulation process and algorithms. Based on a series of subjective tests in a virtual reality environment with various simulation parameters, a fast simulation method with acceptable accuracy has been explored. [Work supported by the European Commission.

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

2002-01-01

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Multiple point least squares equalization in a room

NASA Technical Reports Server (NTRS)

Elliott, S. J.; Nelson, P. A.

1988-01-01

Equalization filters designed to minimize the mean square error between a delayed version of the original electrical signal and the equalized response at a point in a room have previously been investigated. In general, such a strategy degrades the response at positions in a room away from the equalization point. A method is presented for designing an equalization filter by adjusting the filter coefficients to minimize the sum of the squares of the errors between the equalized responses at multiple points in the room and delayed versions of the original, electrical signal. Such an equalization filter can give a more uniform frequency response over a greater volume of the enclosure than can the single point equalizer above. Computer simulation results are presented of equalizing the frequency responses from a loudspeaker to various typical ear positions, in a room with dimensions and acoustic damping typical of a car interior, using the two approaches outlined above. Adaptive filter algorithms, which can automatically adjust the coefficients of a digital equalization filter to achieve this minimization, will also be discussed.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

Hydrological regionalisation based on available hydrological information for runoff prediction at catchment scale

NASA Astrophysics Data System (ADS)

Li, Qiaoling; Li, Zhijia; Zhu, Yuelong; Deng, Yuanqian; Zhang, Ke; Yao, Cheng

2018-06-01

Regionalisation provides a way of transferring hydrological information from gauged to ungauged catchments. The past few decades has seen several kinds of regionalisation approaches for catchment classification and runoff predictions. The underlying assumption is that catchments having similar catchment properties are hydrological similar. This requires the appropriate selection of catchment properties, particularly the inclusion of observed hydrological information, to explain the similarity of hydrological behaviour. We selected observable catchments properties and flow duration curves to reflect the hydrological behaviour, and to regionalize rainfall-runoff response for runoff prediction. As a case study, we investigated 15 catchments located in the Yangtze and Yellow River under multiple hydro-climatic conditions. A clustering scheme was developed to separate the catchments into 4 homogeneous regions by employing catchment properties including hydro-climatic attributes, topographic attributes and land cover etc. We utilized daily flow duration curves as the indicator of hydrological response and interpreted hydrological similarity by root mean square errors. The combined analysis of similarity in catchment properties and hydrological response suggested that catchments in the same homogenous region were hydrological similar. A further validation was conducted by establishing a rainfall-runoff coaxial correlation diagram for each catchment. A common coaxial correlation diagram was generated for each homogenous region. The performances of most coaxial correlation diagrams met the national standard. The coaxial correlation diagram can be transferred within the homogeneous region for runoff prediction in ungauged catchments at an hourly time scale.

Functional Capacity of Patients with Pacemaker Due to Isolated Congenital Atrioventricular Block

PubMed Central

de Oliveira Júnior, Roberto Márcio; da Silva, Kátia Regina; Kawauchi, Tatiana Satie; Alves, Lucas Bassolli de Oliveira; Crevelari, Elizabeth Sartori; Martinelli, Martino; Costa, Roberto

2015-01-01

Background Isolated congenital atrioventricular block (CAVB) is a rare condition with multiple clinical outcomes. Ventricular remodeling can occur in approximately 10% of the patients after pacemaker (PM) implantation. Objectives To assess the functional capacity of children and young adults with isolated CAVB and chronic pacing of the right ventricle (RV) and evaluate its correlation with predictors of ventricular remodeling. Methods This cross-sectional study used a cohort of patients with isolated CAVB and RV pacing for over a year. The subjects underwent clinical and echocardiographic evaluation. Functional capacity was assessed using the six-minute walk test. Chi-square test, Fisher's exact test, and Pearson correlation coefficient were used, considering a significance level of 5%. Results A total of 61 individuals were evaluated between March 2010 and December 2013, of which 67.2% were women, aged between 7 and 41 years, who were using PMs for 13.5 ± 6.3 years. The percentage of ventricular pacing was 97.9 ± 4.1%, and the duration of the paced QRS complex was 153.7 ± 19.1 ms. Majority of the subjects (95.1%) were asymptomatic and did not use any medication. The mean distance walked was 546.9 ± 76.2 meters and was strongly correlated with the predicted distance (r = 0.907, p = 0.001) but not with risk factors for ventricular remodeling. Conclusions The functional capacity of isolated CAVB patients with chronic RV pacing was satisfactory but did not correlate with risk factors for ventricular remodeling. PMID:25387405

Demonstration of the Web-based Interspecies Correlation Estimation (Web-ICE) modeling application

EPA Science Inventory

The Web-based Interspecies Correlation Estimation (Web-ICE) modeling application is available to the risk assessment community through a user-friendly internet platform (http://epa.gov/ceampubl/fchain/webice/). ICE models are log-linear least square regressions that predict acute...

Global correlation of topographic heights and gravity anomalies

NASA Technical Reports Server (NTRS)

Roufosse, M. C.

1977-01-01

The short wavelength features were obtained by subtracting a calculated 24th-degree-and-order field from observed data written in 1 deg x 1 deg squares. The correlation between the two residual fields was examined by a program of linear regression. When run on a worldwide scale over oceans and continents separately, the program did not exhibit any correlation; this can be explained by the fact that the worldwide autocorrelation function for residual gravity anomalies falls off much faster as a function of distance than does that for residual topographic heights. The situation was different when the program was used in restricted areas, of the order of 5 deg x 5 deg square. For 30% of the world,fair-to-good correlations were observed, mostly over continents. The slopes of the regression lines are proportional to apparent densities, which offer a large spectrum of values that are being interpreted in terms of features in the upper mantle consistent with available heat-flow, gravity, and seismic data.

Electrohydrodynamic (EHD) drying of the Chinese wolfberry fruits.

PubMed

Yang, Maosheng; Ding, Changjiang

2016-01-01

The conventional methods of drying Chinese wolfberry fruits cause loss of active ingredients and the drying time is very long. In order to explore and investigate the new method of drying Chinese wolfberry fruits, electrohydrodynamic (EHD) drying system was used to drying for Chinese wolfberry fruits with a multiple needle-to-plate electrode on five levels alternating voltage at 0, 20, 24, 28 and 32 kV and a multiple needle-to-plate electrode on a level direct voltage at 28 kV. The drying rate, the moisture rate, shrinkage rate, rehydration ratio, and Vitamin C contents of Chinese wolfberry were measured. Ten different mathematical drying models were also determined and compared to simulate drying curves based on the root mean square error, reduced mean square of the deviation and the coefficient of correlation. Each drying treatment was carried out at (25 ± 2) °C, the drying relative humidity was (30 ± 5) % and all samples were dehydrated until they reached the final moisture content (17 ± 1)/100 g. The results showed that the drying rate of Chinese wolfberry was notably greater in the EHD system when compared to control, and improved by 1.8777, 2.0017, 2.3676 and 2.6608 times, respectively, at 20, 24, 28 and 32 kV, compared to that of the control in the 5 h. The drying rate with multiple needles-to-plate electrode under AC electric field is faster than that with a multiple needle-to-plate electrode under DC electric field and the mass transfer enhancement factor heightened with the increase of voltage. The EHD drying treatments have a significant effect on rehydration ratio, and Vitamin C contents of Chinese wolfberry, but no significant differences was observed in shrinkage rate of Chinese wolfberry. The specific energy consumption of EHD drying (kJ·kg(-1) water) were significantly influenced by the alternating voltage, it heightened with the increase of voltage. The Parabolic model was best suited for describing the drying rate curve of Chinese wolfberry fruits. Therefore, this work presents a facile and effective clue for experimentally and theoretically determining the EHD drying properties of Chinese wolfberry.

Tantalum films with well-controlled roughness grown by oblique incidence deposition

NASA Astrophysics Data System (ADS)

Rechendorff, K.; Hovgaard, M. B.; Chevallier, J.; Foss, M.; Besenbacher, F.

2005-08-01

We have investigated how tantalum films with well-controlled surface roughness can be grown by e-gun evaporation with oblique angle of incidence between the evaporation flux and the surface normal. Due to a more pronounced shadowing effect the root-mean-square roughness increases from about 2 to 33 nm as grazing incidence is approached. The exponent, characterizing the scaling of the root-mean-square roughness with length scale (α), varies from 0.75 to 0.93, and a clear correlation is found between the angle of incidence and root-mean-square roughness.

DIF Detection Using Multiple-Group Categorical CFA with Minimum Free Baseline Approach

ERIC Educational Resources Information Center

Chang, Yu-Wei; Huang, Wei-Kang; Tsai, Rung-Ching

2015-01-01

The aim of this study is to assess the efficiency of using the multiple-group categorical confirmatory factor analysis (MCCFA) and the robust chi-square difference test in differential item functioning (DIF) detection for polytomous items under the minimum free baseline strategy. While testing for DIF items, despite the strong assumption that all…

Eye Movements during Multiple Object Tracking: Where Do Participants Look?

ERIC Educational Resources Information Center

Fehd, Hilda M.; Seiffert, Adriane E.

2008-01-01

Similar to the eye movements you might make when viewing a sports game, this experiment investigated where participants tend to look while keeping track of multiple objects. While eye movements were recorded, participants tracked either 1 or 3 of 8 red dots that moved randomly within a square box on a black background. Results indicated that…

Analysis of Multiple Contingency Tables by Exact Conditional Tests for Zero Partial Association.

ERIC Educational Resources Information Center

Kreiner, Svend

The tests for zero partial association in a multiple contingency table have gained new importance with the introduction of graphical models. It is shown how these may be performed as exact conditional tests, using as test criteria either the ordinary likelihood ratio, the standard x squared statistic, or any other appropriate statistics. A…

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

Metabolomics of Breast Cancer Using High-Resolution Magic Angle Spinning Magnetic Resonance Spectroscopy: Correlations with 18F-FDG Positron Emission Tomography-Computed Tomography, Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging MRI.

PubMed

Yoon, Haesung; Yoon, Dahye; Yun, Mijin; Choi, Ji Soo; Park, Vivian Youngjean; Kim, Eun-Kyung; Jeong, Joon; Koo, Ja Seung; Yoon, Jung Hyun; Moon, Hee Jung; Kim, Suhkmann; Kim, Min Jung

2016-01-01

Our goal in this study was to find correlations between breast cancer metabolites and conventional quantitative imaging parameters using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) and to find breast cancer subgroups that show high correlations between metabolites and imaging parameters. Between August 2010 and December 2013, we included 53 female patients (mean age 49.6 years; age range 32-75 years) with a total of 53 breast lesions assessed by the Breast Imaging Reporting and Data System. They were enrolled under the following criteria: breast lesions larger than 1 cm in diameter which 1) were suspicious for malignancy on mammography or ultrasound (US), 2) were pathologically confirmed to be breast cancer with US-guided core-needle biopsy (CNB) 3) underwent 3 Tesla MRI with dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and positron emission tomography-computed tomography (PET-CT), and 4) had an attainable immunohistochemistry profile from CNB. We acquired spectral data by HR-MAS MRS with CNB specimens and expressed the data as relative metabolite concentrations. We compared the metabolites with the signal enhancement ratio (SER), maximum standardized FDG uptake value (SUV max), apparent diffusion coefficient (ADC), and histopathologic prognostic factors for correlation. We calculated Spearman correlations and performed a partial least squares-discriminant analysis (PLS-DA) to further classify patient groups into subgroups to find correlation differences between HR-MAS spectroscopic values and conventional imaging parameters. In a multivariate analysis, the PLS-DA models built with HR-MAS MRS metabolic profiles showed visible discrimination between high and low SER, SUV, and ADC. In luminal subtype breast cancer, compared to all cases, high SER, ADV, and SUV were more closely clustered by visual assessment. Multiple metabolites were correlated with SER and SUV in all cases. Multiple metabolites showed correlations with SER and SUV in the ER positive, HER2 negative, and Ki-67 negative groups. High levels of PC, choline, and glycine acquired from HR-MAS MRS using CNB specimens were noted in the high SER group via DCE MRI and the high SUV group via PET-CT, with significant correlations between choline and SER and between PC and SUV. Further studies should investigate whether HR-MAS MRS using CNB specimens can provide similar or more prognostic information than conventional quantitative imaging parameters.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Application of partial least squares near-infrared spectral classification in diabetic identification

NASA Astrophysics Data System (ADS)

Yan, Wen-juan; Yang, Ming; He, Guo-quan; Qin, Lin; Li, Gang

2014-11-01

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum - a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip's NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups - i.e. 53 samples as calibration set and 25 as prediction set - then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

Combinatorics of least-squares trees.

PubMed

Mihaescu, Radu; Pachter, Lior

2008-09-09

A recurring theme in the least-squares approach to phylogenetics has been the discovery of elegant combinatorial formulas for the least-squares estimates of edge lengths. These formulas have proved useful for the development of efficient algorithms, and have also been important for understanding connections among popular phylogeny algorithms. For example, the selection criterion of the neighbor-joining algorithm is now understood in terms of the combinatorial formulas of Pauplin for estimating tree length. We highlight a phylogenetically desirable property that weighted least-squares methods should satisfy, and provide a complete characterization of methods that satisfy the property. The necessary and sufficient condition is a multiplicative four-point condition that the variance matrix needs to satisfy. The proof is based on the observation that the Lagrange multipliers in the proof of the Gauss-Markov theorem are tree-additive. Our results generalize and complete previous work on ordinary least squares, balanced minimum evolution, and the taxon-weighted variance model. They also provide a time-optimal algorithm for computation.

Indices for estimating fractional snow cover in the western Tibetan Plateau

NASA Astrophysics Data System (ADS)

Shreve, Cheney M.; Okin, Gregory S.; Painter, Thomas H.

Snow cover in the Tibetan Plateau is highly variable in space and time and plays a key role in ecological processes of this cold-desert ecosystem. Resolution of passive microwave data is too low for regional-scale estimates of snow cover on the Tibetan Plateau, requiring an alternate data source. Optically derived snow indices allow for more accurate quantification of snow cover using higher-resolution datasets subject to the constraint of cloud cover. This paper introduces a new optical snow index and assesses four optically derived MODIS snow indices using Landsat-based validation scenes: MODIS Snow-Covered Area and Grain Size (MODSCAG), Relative Multiple Endmember Spectral Mixture Analysis (RMESMA), Relative Spectral Mixture Analysis (RSMA) and the normalized-difference snow index (NDSI). Pearson correlation coefficients were positively correlated with the validation datasets for all four optical snow indices, suggesting each provides a good measure of total snow extent. At the 95% confidence level, linear least-squares regression showed that MODSCAG and RMESMA had accuracy comparable to validation scenes. Fusion of optical snow indices with passive microwave products, which provide snow depth and snow water equivalent, has the potential to contribute to hydrologic and energy-balance modeling in the Tibetan Plateau.

Testing Pattern Hypotheses for Correlation Matrices

ERIC Educational Resources Information Center

McDonald, Roderick P.

1975-01-01

The treatment of covariance matrices given by McDonald (1974) can be readily modified to cover hypotheses prescribing zeros and equalities in the correlation matrix rather than the covariance matrix, still with the convenience of the closed-form Least Squares solution and the classical Newton method. (Author/RC)

Numerical methods for comparing fresh and weathered oils by their FTIR spectra.

PubMed

Li, Jianfeng; Hibbert, D Brynn; Fuller, Stephen

2007-08-01

Four comparison statistics ('similarity indices') for the identification of the source of a petroleum oil spill based on the ASTM standard test method D3414 were investigated. Namely, (1) first difference correlation coefficient squared and (2) correlation coefficient squared, (3) first difference Euclidean cosine squared and (4) Euclidean cosine squared. For numerical comparison, an FTIR spectrum is divided into three regions, described as: fingerprint (900-700 cm(-1)), generic (1350-900 cm(-1)) and supplementary (1770-1685 cm(-1)), which are the same as the three major regions recommended by the ASTM standard. For fresh oil samples, each similarity index was able to distinguish between replicate independent spectra of the same sample and between different samples. In general, the two first difference-based indices worked better than their parent indices. To provide samples to reveal relationships between weathered and fresh oils, a simple artificial weathering procedure was carried out. Euclidean cosine and correlation coefficients both worked well to maintain identification of a match in the fingerprint region and the two first difference indices were better in the generic region. Receiver operating characteristic curves (true positive rate versus false positive rate) for decisions on matching using the fingerprint region showed two samples could be matched when the difference in weathering time was up to 7 days. Beyond this time the true positive rate falls and samples cannot be reliably matched. However, artificial weathering of a fresh source sample can aid the matching of a weathered sample to its real source from a pool of very similar candidates.

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution

PubMed Central

Poulin, Robert; Lagrue, Clément

2017-01-01

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance–mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance–mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites. PMID:27994156

Use of Thematic Mapper for water quality assessment

NASA Technical Reports Server (NTRS)

Horn, E. M.; Morrissey, L. A.

1984-01-01

The evaluation of simulated TM data obtained on an ER-2 aircraft at twenty-five predesignated sample sites for mapping water quality factors such as conductivity, pH, suspended solids, turbidity, temperature, and depth, is discussed. Using a multiple regression for the seven TM bands, an equation is developed for the suspended solids. TM bands 1, 2, 3, 4, and 6 are used with logarithm conductivity in a multiple regression. The assessment of regression equations for a high coefficient of determination (R-squared) and statistical significance is considered. Confidence intervals about the mean regression point are calculated in order to assess the robustness of the regressions used for mapping conductivity, turbidity, and suspended solids, and by regressing random subsamples of sites and comparing the resultant range of R-squared, cross validation is conducted.

A channel estimation scheme for MIMO-OFDM systems

NASA Astrophysics Data System (ADS)

He, Chunlong; Tian, Chu; Li, Xingquan; Zhang, Ce; Zhang, Shiqi; Liu, Chaowen

2017-08-01

In view of the contradiction of the time-domain least squares (LS) channel estimation performance and the practical realization complexity, a reduced complexity channel estimation method for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) based on pilot is obtained. This approach can transform the complexity of MIMO-OFDM channel estimation problem into a simple single input single output-orthogonal frequency division multiplexing (SISO-OFDM) channel estimation problem and therefore there is no need for large matrix pseudo-inverse, which greatly reduces the complexity of algorithms. Simulation results show that the bit error rate (BER) performance of the obtained method with time orthogonal training sequences and linear minimum mean square error (LMMSE) criteria is better than that of time-domain LS estimator and nearly optimal performance.

Correlation of published data on the solubility of methane in H/sub 2/O-NaCl solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coco, L.T.; Johnson, A.E. Jr.; Bebout, D.G.

1981-01-01

A new correlation of the available published data for the solubility of methane in water was developed, based on fundamental thermodynamic relationships. An empirical relationship for the salting-out coefficient of NaCl for methane solubility in water was determined as a function of temperature. Root mean square and average deviations for the new correlation, the Haas correlation, and the revised Blount equation are compared.

Interband magneto-spectroscopy in InSb square and parabolic quantum wells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kasturiarachchi, T.; Edirisooriya, M.; Mishima, T. D.

We measure the magneto-optical absorption due to intersubband optical transitions between conduction and valence subband Landau levels in InSb square and parabolic quantum wells. InSb has the narrowest band gap (0.24 eV at low temperature) of the III–V semiconductors leading to a small effective mass (0.014 m{sub 0}) and a large g–factor (−51). As a result, the Landau level spacing is large at relatively small magnetic fields (<8 T), and one can observe spin-splitting of the Landau levels. We examine two structures: (i) a multiple-square-well structure and (ii) a structure containing multiple parabolic wells. The energies and intensities of the strongest featuresmore » are well explained by a modified Pidgeon-Brown model based on an 8-band k•p model that explicitly incorporates pseudomorphic strain. The strain is essential for obtaining agreement between theory and experiment. While modeling the square well is relatively straight-forward, the parabolic well consists of 43 different layers of various thickness to approximate a parabolic potential. Agreement between theory and experiment for the parabolic well validates the applicability of the model to complicated structures, which demonstrates the robustness of our model and confirms its relevance for developing electronic and spintronic devices that seek to exploit the properties of the InSb band structure.« less

De-noising of 3D multiple-coil MR images using modified LMMSE estimator.

PubMed

Yaghoobi, Nima; Hasanzadeh, Reza P R

2018-06-20

De-noising is a crucial topic in Magnetic Resonance Imaging (MRI) which focuses on less loss of Magnetic Resonance (MR) image information and details preservation during the noise suppression. Nowadays multiple-coil MRI system is preferred to single one due to its acceleration in the imaging process. Due to the fact that the model of noise in single-coil and multiple-coil MRI systems are different, the de-noising methods that mostly are adapted to single-coil MRI systems, do not work appropriately with multiple-coil one. The model of noise in single-coil MRI systems is Rician while in multiple-coil one (if no subsampling occurs in k-space or GRAPPA reconstruction process is being done in the coils), it obeys noncentral Chi (nc-χ). In this paper, a new filtering method based on the Linear Minimum Mean Square Error (LMMSE) estimator is proposed for multiple-coil MR Images ruined by nc-χ noise. In the presented method, to have an optimum similarity selection of voxels, the Bayesian Mean Square Error (BMSE) criterion is used and proved for nc-χ noise model and also a nonlocal voxel selection methodology is proposed for nc-χ distribution. The results illustrate robust and accurate performance compared to the related state-of-the-art methods, either on ideal nc-χ images or GRAPPA reconstructed ones. Copyright © 2018. Published by Elsevier Inc.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

Development of the Modified Four Square Step Test and its reliability and validity in people with stroke.

PubMed

Roos, Margaret A; Reisman, Darcy S; Hicks, Gregory; Rose, William; Rudolph, Katherine S

2016-01-01

Adults with stroke have difficulty avoiding obstacles when walking, especially when a time constraint is imposed. The Four Square Step Test (FSST) evaluates dynamic balance by requiring individuals to step over canes in multiple directions while being timed, but many people with stroke are unable to complete it. The purposes of this study were to (1) modify the FSST by replacing the canes with tape so that more persons with stroke could successfully complete the test and (2) examine the reliability and validity of the modified version. Fifty-five subjects completed the Modified FSST (mFSST) by stepping over tape in all four directions while being timed. The mFSST resulted in significantly greater numbers of subjects completing the test than the FSST (39/55 [71%] and 33/55 [60%], respectively) (p < 0.04). The test-retest, intrarater, and interrater reliability of the mFSST were excellent (intraclass correlation coefficient ranges: 0.81-0.99). Construct and concurrent validity of the mFSST were also established. The minimal detectable change was 6.73 s. The mFSST, an ideal measure of dynamic balance, can identify progress in people with stroke in varied settings and can be completed by a wide range of people with stroke in approximately 5 min with the use of minimal equipment (tape, stop watch).

Mapping the Sensitivity of the Public Emotion to the Movement of STOCK Market Value: a Case Study of Manhattan

NASA Astrophysics Data System (ADS)

Kang, Y.; Wang, J.; Wang, Y.; Angsuesser, S.; Fei, T.

2017-09-01

We examined whether emotion expressed by users in social media can be influenced by stock market index or can predict the fluctuation of the stock market index. We collected the emotion data by using face detection technology and emotion cognition services for photos uploaded to Flickr. Each face's emotion was described in 8 dimensions the location was also recorded. An emotion score index was defined based on the combination of all 8 dimensions of emotion calculated by principal component analysis. The correlation coefficients between the stock market values and emotion scores are significant (R > 0.59 with p < 0.01). Using Granger Causality analysis for cause and effect detection, we found that users' emotion is influenced by stock market value change. A multiple linear regression model was established (R-square = 0.76) to explore the potential factors that influence the emotion score. Finally, a sensitivity map was created to show sensitive areas where human emotion is easily affected by the stock market changes. We concluded that in Manhattan region: (1) there is an obvious relationship between human emotion and stock market fluctuation; (2) emotion change follows the movements of the stock market; (3) the Times Square and Broadway Theatre are the most sensitive regions in terms of public emotional reaction to the economy represented by stock value.

Estimation of reliability of predictions and model applicability domain evaluation in the analysis of acute toxicity (LD50).

PubMed

Sazonovas, A; Japertas, P; Didziapetris, R

2010-01-01

This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.

Role of assessment tests in the stability of intelligence scoring of pre-school children with uneven/delayed cognitive profile.

PubMed

Yang, P; Jong, Y-J; Hsu, H-Y; Lung, F-W

2011-05-01

As part of an ongoing clinical service programme for pre-school children with developmental delay in an Asian developing country, we analysed the effect of three assessment tests, that is, Bayley Scale of Infant Development-II, Leiter International Performance Scale - Revised and Wechsler Preschool and Primary Scale of Intelligence - Revised - Chinese, on the stability of intelligence quotient (IQ) of children from pre-school through early childhood. The participants were 313 Taiwanese pre-school children with uneven or delayed cognitive profile and they were followed through early childhood. IQ stability was explored by different tests and among children of different clinical diagnosis: 168 children with non-autistic intellectual disability, 73 children with autism spectrum disorder, 58 children with mixed receptive-expressive language disorder and 14 children of other heterogeneous diagnoses. Stability of scores was evaluated using the r-squared for Pearson's coefficients to see the correlation between initial IQ (IQ1) and follow-up IQ (IQ2). Multiple linear regressions were also applied to see whether IQ1 had predictive ability for IQ2 and test-test difference in the total 313 children and each diagnostic subgroup. Results revealed that mean IQ1 was 65.8 ± 15.4 while mean IQ2 was 73.2 ± 17.9 for the total 313 children. The IQs were stable across an average follow-up duration of 38.6 ± 22.1 month from pre-school into early childhood. Patterns of positive correlations between IQ1 and IQ2 were noted by all the tests (r-squared = 0.43-0.5, all P < 0.001) and in the majority of diagnostic subgroups. Multiple regressions analysis also revealed that IQ1 could predict IQ2 significantly in all the tests (all P < 0.001). After careful choice of appropriate initial test, stability of IQ in children with developmental delay was noted from pre-school through early childhood. In addition, the translated version of cognitive assessment was valid for the required context of an Asian developing country. With the current emphasis on early identification and intervention for pre-school children with developmental delay, this information bears merit in clinical practice. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

Quantitative structure-activity relationship study of antioxidative peptide by using different sets of amino acids descriptors

NASA Astrophysics Data System (ADS)

Li, Yao-Wang; Li, Bo; He, Jiguo; Qian, Ping

2011-07-01

A database consisting of 214 tripeptides which contain either His or Tyr residue was applied to study quantitative structure-activity relationships (QSAR) of antioxidative tripeptides. Partial Least-Squares Regression analysis (PLSR) was conducted using parameters individually of each amino acid descriptor, including Divided Physico-chemical Property Scores (DPPS), Hydrophobic, Electronic, Steric, and Hydrogen (HESH), Vectors of Hydrophobic, Steric, and Electronic properties (VHSE), Molecular Surface-Weighted Holistic Invariant Molecular (MS-WHIM), isotropic surface area-electronic charge index (ISA-ECI) and Z-scale, to describe antioxidative tripeptides as X-variables and antioxidant activities measured with ferric thiocyanate methods were as Y-variable. After elimination of outliers by Hotelling's T 2 method and residual analysis, six significant models were obtained describing the entire data set. According to cumulative squared multiple correlation coefficients ( R2), cumulative cross-validation coefficients ( Q2) and relative standard deviation for calibration set (RSD c), the qualities of models using DPPS, HESH, ISA-ECI, and VHSE descriptors are better ( R2 > 0.6, Q2 > 0.5, RSD c < 0.39) than that of models using MS-WHIM and Z-scale descriptors ( R2 < 0.6, Q2 < 0.5, RSD c > 0.44). Furthermore, the predictive ability of models using DPPS descriptor is best among the six descriptors systems (cumulative multiple correlation coefficient for predict set ( Rext2) > 0.7). It was concluded that the DPPS is better to describe the amino acid of antioxidative tripeptides. The results of DPPS descriptor reveal that the importance of the center amino acid and the N-terminal amino acid are far more than the importance of the C-terminal amino acid for antioxidative tripeptides. The hydrophobic (positively to activity) and electronic (negatively to activity) properties of the N-terminal amino acid are suggested to play the most important significance to activity, followed by the hydrogen bond (positively to activity) of the center amino acid. The N-terminal amino acid should be a high hydrophobic and low electronic amino acid (such as Ala, Gly, Val, and Leu); the center amino acid would be an amino acid that possesses high hydrogen bond property (such as base amino acid Arg, Lys, and His). The structural characteristics of antioxidative peptide be found in this paper may contribute to the further research of antioxidative mechanism.

Sequential Least-Squares Using Orthogonal Transformations. [spacecraft communication/spacecraft tracking-data smoothing

NASA Technical Reports Server (NTRS)

Bierman, G. J.

1975-01-01

Square root information estimation, starting from its beginnings in least-squares parameter estimation, is considered. Special attention is devoted to discussions of sensitivity and perturbation matrices, computed solutions and their formal statistics, consider-parameters and consider-covariances, and the effects of a priori statistics. The constant-parameter model is extended to include time-varying parameters and process noise, and the error analysis capabilities are generalized. Efficient and elegant smoothing results are obtained as easy consequences of the filter formulation. The value of the techniques is demonstrated by the navigation results that were obtained for the Mariner Venus-Mercury (Mariner 10) multiple-planetary space probe and for the Viking Mars space mission.

Least-Squares Self-Calibration of Imaging Array Data

NASA Technical Reports Server (NTRS)

Arendt, R. G.; Moseley, S. H.; Fixsen, D. J.

2004-01-01

When arrays are used to collect multiple appropriately-dithered images of the same region of sky, the resulting data set can be calibrated using a least-squares minimization procedure that determines the optimal fit between the data and a model of that data. The model parameters include the desired sky intensities as well as instrument parameters such as pixel-to-pixel gains and offsets. The least-squares solution simultaneously provides the formal error estimates for the model parameters. With a suitable observing strategy, the need for separate calibration observations is reduced or eliminated. We show examples of this calibration technique applied to HST NICMOS observations of the Hubble Deep Fields and simulated SIRTF IRAC observations.

Quality of life, symptom distress, and social support among renal transplant recipients in Southern Taiwan: a correlational study.

PubMed

Chen, Wan-Chi; Chen, Ching-Huey; Lee, Po-Chang; Wang, Wen-Ling

2007-12-01

Quality of life is an important indicator for evaluating therapeutic outcomes and mortality in patients with end-stage renal disease. Few studies have explored the impact of symptom distress and social support on quality of life in this population. A correlational study was designed to examine the influence of symptom distress, social support and demographic characteristics on quality of life in renal transplant recipients. A convenience sample of 113 renal transplant recipients was recruited from a medical center in Southern Taiwan. A structured questionnaire was used to collect data. This four-part tool included: Quality of Life Index--Kidney Transplant Version III, Physical Symptom Distress Scale, Social Support Scale, and demographic characteristics. Data were analyzed by descriptive and inferential statistics (SPSS 10.1 statistical package). Percentage, rank, mean and standard deviation, t-tests, chi-square, ANOVA, Pearson's correlation and multiple regression were computed. Results showed that renal transplant recipients had a moderate quality of life. Social support and symptom distress, age, employment status, and household income significantly explained 28.8% of the variance in quality of life. Findings suggest implications for interventional programming and research aimed toward improving quality of life, including individual and family-based approaches designed to enhance recipients' social support and address effective management of symptoms. Recruiting a transplant clinical nurse specialist to design and implement an intervention program also is recommended.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

A Count Model to Study the Correlates of 60 Min of Daily Physical Activity in Portuguese Children

PubMed Central

Borges, Alessandra; Gomes, Thayse Natacha; Santos, Daniel; Pereira, Sara; dos Santos, Fernanda K.; Chaves, Raquel; Katzmarzyk, Peter T.; Maia, José

2015-01-01

This study aimed to present data on Portuguese children (aged 9–11 years) complying with moderate-to-vigorous physical activity (MVPA) guidelines, and to identify the importance of correlates from multiple domains associated with meeting the guidelines. Physical activity (PA) was objectively assessed by accelerometry throughout seven days on 777 children. A count model using Poisson regression was used to identify the best set of correlates that predicts the variability in meeting the guidelines. Only 3.1% of children met the recommended daily 60 min of MVPA for all seven days of the week. Further, the Cochrane–Armitage chi-square test indicated a linear and negative trend (p < 0.001) from none to all seven days of children complying with the guidelines. The count model explained 22% of the variance in meeting MVPA guidelines daily. Being a girl, having a higher BMI, belonging to families with higher income, sleeping more and taking greater time walking from home to a sporting venue significantly reduced the probability of meeting daily recommended MVPA across the seven days. Furthermore, compared to girls, increasing sleep time in boys increased their chances of compliance with the MVPA recommendations. These results reinforce the relevance of considering different covariates’ roles on PA compliance when designing efficient intervention strategies to promote healthy and active lifestyles in children. PMID:25730296

A count model to study the correlates of 60 min of daily physical activity in Portuguese children.

PubMed

Borges, Alessandra; Gomes, Thayse Natacha; Santos, Daniel; Pereira, Sara; dos Santos, Fernanda K; Chaves, Raquel; Katzmarzyk, Peter T; Maia, José

2015-02-26

This study aimed to present data on Portuguese children (aged 9-11 years) complying with moderate-to-vigorous physical activity (MVPA) guidelines, and to identify the importance of correlates from multiple domains associated with meeting the guidelines. Physical activity (PA) was objectively assessed by accelerometry throughout seven days on 777 children. A count model using Poisson regression was used to identify the best set of correlates that predicts the variability in meeting the guidelines. Only 3.1% of children met the recommended daily 60 min of MVPA for all seven days of the week. Further, the Cochrane-Armitage chi-square test indicated a linear and negative trend (p<0.001) from none to all seven days of children complying with the guidelines. The count model explained 22% of the variance in meeting MVPA guidelines daily. Being a girl, having a higher BMI, belonging to families with higher income, sleeping more and taking greater time walking from home to a sporting venue significantly reduced the probability of meeting daily recommended MVPA across the seven days. Furthermore, compared to girls, increasing sleep time in boys increased their chances of compliance with the MVPA recommendations. These results reinforce the relevance of considering different covariates' roles on PA compliance when designing efficient intervention strategies to promote healthy and active lifestyles in children.

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments.

PubMed

Boomer, Kathleen B; Weller, Donald E; Jordan, Thomas E

2008-01-01

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.

High-resolution imaging of basal cell carcinoma: a comparison between multiphoton microscopy with fluorescence lifetime imaging and reflectance confocal microscopy.

PubMed

Manfredini, Marco; Arginelli, Federica; Dunsby, Christopher; French, Paul; Talbot, Clifford; König, Karsten; Pellacani, Giovanni; Ponti, Giovanni; Seidenari, Stefania

2013-02-01

The aim of this study was to compare morphological aspects of basal cell carcinoma (BCC) as assessed by two different imaging methods: in vivo reflectance confocal microscopy (RCM) and multiphoton tomography with fluorescence lifetime imaging implementation (MPT-FLIM). The study comprised 16 BCCs for which a complete set of RCM and MPT-FLIM images were available. The presence of seven MPT-FLIM descriptors was evaluated. The presence of seven RCM equivalent parameters was scored in accordance to their extension. Chi-squared test with Fisher's exact test and Spearman's rank correlation coefficient were determined between MPT-FLIM scores and adjusted-RCM scores. MPT-FLIM and RCM descriptors of BCC were coupled to match the descriptors that define the same pathological structures. The comparison included: Streaming and Aligned elongated cells, Streaming with multiple directions and Double alignment, Palisading (RCM) and Palisading (MPT-FLIM), Typical tumor islands, and Cell islands surrounded by fibers, Dark silhouettes and Phantom islands, Plump bright cells and Melanophages, Vessels (RCM), and Vessels (MPT-FLIM). The parameters that were significantly correlated were Melanophages/Plump Bright Cells, Aligned elongated cells/Streaming, Double alignment/Streaming with multiple directions, and Palisading (MPT-FLIM)/Palisading (RCM). According to our data, both methods are suitable to image BCC's features. The concordance between MPT-FLIM and RCM is high, with some limitations due to the technical differences between the two devices. The hardest difficulty when comparing the images generated by the two imaging modalities is represented by their different field of view. © 2012 John Wiley & Sons A/S.

Scattering of Internal Tides by Irregular Bathymetry of Large Extent

NASA Astrophysics Data System (ADS)

Mei, C.

2014-12-01

We present an analytic theory of scattering of tide-generated internal gravity waves in a continuously stratified ocean with a randomly rough seabed. Based on the linearized approximation, the idealized case of constant mean sea depth and Brunt-Vaisala frequency is considered. The depth fluctuation is assumed to be a stationary random function of space characterized by small amplitude and correlation length comparable to the typical wavelength. For both one- and two-dimensional topography the effects of scattering on wave phase over long distances are derived explicitly by the method of multiple scales. For one-dimensional topography, numerical results are compared with Buhler-& Holmes-Cerfon(2011) computed by the method of characteristics. For two-dimensional topography, new results are presented for both statistically isotropic and anisotropic cases. In thi talk we shall apply the perturbation technique of multiple scales to treat analytically the random scattering of internal tides by gently sloped bathymetric irregularities.The basic assumptions are: incompressible fluid, infinitestimal wave amplitudes, constant Brunt-Vaisala frequency, and constant mean depth. In addition, the depth disorder is assumed to be a stationary random function of space with zero mean and small root-mean-square amplitude. The correlation length can be comparable in order of magnitude as the dominant wavelength. Both one- and two-dimensional disorder will be considered. Physical effects of random scattering on the mean wave phase i.e., spatial attenuation and wavenumber shift will be calculated and discussed for one mode of incident wave. For two dimensional topographies, statistically isotropic and anisotropic examples will be presented.

The ecology of prescription opioid abuse in the USA: geographic variation in patients’ use of multiple prescribers (“doctor shopping”)

PubMed Central

McDonald, Douglas C.; Carlson, Kenneth E.

2016-01-01

Purpose This study estimates the prevalence in US counties of opioid patients who use large numbers of prescribers, the amounts of opioids they obtain, and the extent to which their prevalence is predicted by ecological attributes of counties, including general medical exposure to opioids. Methods Finite mixture models were used to estimate the size of an outlier subpopulation of patients with suspiciously large numbers of prescribers (probable doctor shoppers), using a sample of 146 million opioid prescriptions dispensed during 2008. Ordinary least squares regression models of county-level shopper rates included independent variables measuring ecological attributes of counties, including rates of patients prescribed opioids, socioeconomic characteristics of the resident population, supply of physicians, and measures of healthcare service utilization. Results The prevalence of shoppers varied widely by county, with rates ranging between 0.6 and 2.5 per 1000 residents. Shopper prevalence was strongly correlated with opioid prescribing for the general population, accounting for 30% of observed county variation in shopper prevalence, after adjusting for physician supply, emergency department visits, in-patient hospital days, poverty rates, percent of county residents living in urban areas, and racial/ethnic composition of resident populations. Approximately 30% of shoppers obtained prescriptions in multiple states. Conclusions The correlation between prevalence of doctor shoppers and opioid patients in a county could indicate either that easy access to legitimate medical treatment raises the risk of abuse or that drug abusers take advantage of greater opportunities in places where access is easy. Approaches to preventing excessive use of different prescribers are discussed. PMID:25111716

Analysis of the wobbling effect in a lens-shaped body rotation

NASA Astrophysics Data System (ADS)

Kim, Minho

2017-03-01

We discuss the wobbling motion in a lens-shaped body rotation, focusing on the frequencies and the amplitude of nutation by filming the rotational motion and wobbling of the body. The friction coefficient of the surface is altered to examine its influence for two lenses with different curvature radii. MATLAB programs are developed to retrieve the Euler angles, which are graphed according to time. It is shown that the lens with a smaller curvature radius exhibits the wobbling effect in all cases, whereas the lens with a larger curvature radius shows such behaviour in limited circumstances. The study confirms that the friction coefficient has a negative linear correlation with the vertical axis declination amplitude with the R-squared value 0.878, showing that friction gives damping and causes smaller axis declination amplitudes. Negative linear correlation also exists with relation to the number of wobbles before the motion stops, where the R-squared value is 0.938, providing further evidence that friction and wobbling cause higher energy dissipation rates. The frequency of the wobbling motion only has a correlation with the curvature radius of the lens, showing no explicit correlation with the friction coefficient, with its R-squared value being 0.077. No losses of contact were observable in this motion. The overall process does not utilize particularly expensive apparatus and will be applicable for senior undergraduate students to experiment on and analyze the motion of a special situation regarding a rigid body that is both spinning and nutating.

On the role of structure-dynamic relationship in determining the excess entropy of mixing and chemical ordering in binary square-well liquid alloys

NASA Astrophysics Data System (ADS)

Lalneihpuii, R.; Shrivastava, Ruchi; Mishra, Raj Kumar

2018-05-01

Using statistical mechanical model with square-well (SW) interatomic potential within the frame work of mean spherical approximation, we determine the composition dependent microscopic correlation functions, interdiffusion coefficients, surface tension and chemical ordering in Ag-Cu melts. Further Dzugutov universal scaling law of normalized diffusion is verified with SW potential in binary mixtures. We find that the excess entropy scaling law is valid for SW binary melts. The partial and total structure factors in the attractive and repulsive regions of the interacting potential are evaluated and then Fourier transformed to get partial and total radial distribution functions. A good agreement between theoretical and experimental values for total structure factor and the reduced radial distribution function are observed, which consolidates our model calculations. The well-known Bhatia-Thornton correlation functions are also computed for Ag-Cu melts. The concentration-concentration correlations in the long wavelength limit in liquid Ag-Cu alloys have been analytically derived through the long wavelength limit of partial correlation functions and apply it to demonstrate the chemical ordering and interdiffusion coefficients in binary liquid alloys. We also investigate the concentration dependent viscosity coefficients and surface tension using the computed diffusion data in these alloys. Our computed results for structure, transport and surface properties of liquid Ag-Cu alloys obtained with square-well interatomic interaction are fully consistent with their corresponding experimental values.

Web-based Interspecies Correlation Estimation (Web-ICE) for Acute Toxicity: User Manual Version 3.1

EPA Science Inventory

Predictive toxicological models are integral to ecological risk assessment because data for most species are limited. Web-based Interspecies Correlation Estimation (Web-ICE) models are least square regressions that predict acute toxicity (LC50/LD50) of a chemical to a species, ge...

WEB-BASED INTERSPECIES CORRELATION ESTIMATION (WEB-ICE) FOR ACUTE TOXICITY: USER MANUAL V2

EPA Science Inventory

Predictive toxicological models are integral to environmental risk Assessment where data for most species are limited. Web-based Interspecies Correlation Estimation (Web-ICE) models are least square regressions that predict acute toxicity (LC50/LD50) of a chemical to a species, ...

A HIGHLY ELONGATED PROMINENT LENS AT z = 0.87: FIRST STRONG-LENSING ANALYSIS OF EL GORDO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zitrin, Adi; Menanteau, Felipe; Hughes, John P.

We present the first strong-lensing (SL) analysis of the galaxy cluster ACT-CL J0102-4915 (El Gordo), in recent HST/ACS images, revealing a prominent strong lens at a redshift of z = 0.87. This finding adds to the already-established unique properties of El Gordo: it is the most massive, hot, X-ray luminous, and bright Sunyaev-Zeldovich effect cluster at z {approx}> 0.6, and the only {sup b}ullet{sup -}like merging cluster known at these redshifts. The lens consists of two merging massive clumps, where, for a source redshift of z{sub s} {approx} 2, each clump exhibits only a small, separate critical area, with amore » total area of 0.69 {+-} 0.11{open_square}' over the two clumps. For a higher source redshift, z{sub s} {approx} 4, the critical curves of the two clumps merge together into one bigger and very elongated lens (axis ratio {approx_equal} 5.5), enclosing an effective area of 1.44 {+-} 0.22{open_square}'. The critical curves continue expanding with increasing redshift so that for high-redshift sources (z{sub s} {approx}> 9) they enclose an area of {approx}1.91 {+-} 0.30{open_square}' (effective {theta}{sub e} {approx_equal} 46.''8 {+-} 3.''7) and a mass of 6.09 {+-} 1.04 Multiplication-Sign 10{sup 14} M{sub Sun }. According to our model, the area of high magnification ({mu} > 10) for such high-redshift sources is {approx_equal}1.2{open_square}', and the area with {mu} > 5 is {approx_equal}2.3{open_square}', making El Gordo a compelling target for studying the high-redshift universe. We obtain a strong lower limit on the total mass of El Gordo, {approx}> 1.7 Multiplication-Sign 10{sup 15} M{sub Sun} from the SL regime alone, suggesting a total mass of roughly M{sub 200} {approx} 2.3 Multiplication-Sign 10{sup 15} M{sub Sun }. Our results should be revisited when additional spectroscopic and HST imaging data are available.« less

Correlation diagrams in 40 Ar/39Ar dating: is there a correct choice?

USGS Publications Warehouse

Dalrymple, G.B.; Lanphere, M.A.; Pringle, M.S.

1988-01-01

Contrary to published assertions, the 2 types of correlation diagrams used in the interpretation of 40Ar/39Ar incremental-heating data yield the same information provided the correct mathematics are used for estimating correlation coefficients and for the least squares fit. The choice is simply between 2 illustrative, graphical displays, neither of which is fundamentally superior to the other. -Authors

Wrong Answers on Multiple-Choice Achievement Tests: Blind Guesses or Systematic Choices?.

ERIC Educational Resources Information Center

Powell, J. C.

A multi-faceted model for the selection of answers for multiple-choice tests was developed from the findings of a series of exploratory studies. This model implies that answer selection should be curvilinear. A series of models were tested for fit using the chi square procedure. Data were collected from 359 elementary school students ages 9-12.…

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

PubMed

Farina, Dario; Leclerc, Frédéric; Arendt-Nielsen, Lars; Buttelli, Olivier; Madeleine, Pascal

2008-02-01

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean+/-SD, percent change 2.0+/-1.6%; P<0.0001) and the center of gravity moved in the cranial direction (shift 11.2+/-6.1mm; P<0.0001) with respect to the beginning of the contraction. The shift in the center of gravity was positively correlated with endurance time (R(2)=0.46, P<0.05), thus subjects with larger shift in the activity map showed longer endurance time. The percent variation in average (over the grid) root mean square was positively correlated with the shift in the center of gravity (R(2)=0.51, P<0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R(2)=0.54 and R(2)=0.56, respectively; P<0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction.

Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003more » and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.« less

Technical Note: Using k-means clustering to determine the number and position of isocenters in MLC-based multiple target intracranial radiosurgery.

PubMed

Yock, Adam D; Kim, Gwe-Ya

2017-09-01

To present the k-means clustering algorithm as a tool to address treatment planning considerations characteristic of stereotactic radiosurgery using a single isocenter for multiple targets. For 30 patients treated with stereotactic radiosurgery for multiple brain metastases, the geometric centroids and radii of each met were determined from the treatment planning system. In-house software used this as well as weighted and unweighted versions of the k-means clustering algorithm to group the targets to be treated with a single isocenter, and to position each isocenter. The algorithm results were evaluated using within-cluster sum of squares as well as a minimum target coverage metric that considered the effect of target size. Both versions of the algorithm were applied to an example patient to demonstrate the prospective determination of the appropriate number and location of isocenters. Both weighted and unweighted versions of the k-means algorithm were applied successfully to determine the number and position of isocenters. Comparing the two, both the within-cluster sum of squares metric and the minimum target coverage metric resulting from the unweighted version were less than those from the weighted version. The average magnitudes of the differences were small (-0.2 cm 2 and 0.1% for the within cluster sum of squares and minimum target coverage, respectively) but statistically significant (Wilcoxon signed-rank test, P < 0.01). The differences between the versions of the k-means clustering algorithm represented an advantage of the unweighted version for the within-cluster sum of squares metric, and an advantage of the weighted version for the minimum target coverage metric. While additional treatment planning considerations have a large influence on the final treatment plan quality, both versions of the k-means algorithm provide automatic, consistent, quantitative, and objective solutions to the tasks associated with SRS treatment planning using a single isocenter for multiple targets. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Selection of lasing direction in single mode semiconductor square ring cavities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Jin-Woong; Kim, Kyoung-Youm; Moon, Hee-Jong

We propose and demonstrate a selection scheme of lasing direction by imposing a loss imbalance structure into the single mode square ring cavity. The control of the traveling direction is realized by introducing a taper-step section in one of the straight waveguides of the square ring cavity. It was shown by semi-analytic calculation that the taper-step section in the cavity provides effective loss imbalance between two travelling directions as the round trip repeats. Various kinds of square cavities were fabricated using InGaAsP/InGaAs multiple quantum well semiconductor materials in order to test the direction selectivity while maintaining the single mode. Wemore » also measured the pump power dependent lasing spectra to investigate the maintenance property of the lasing direction. The experimental results demonstrated that the proposed scheme is an efficient means for a unidirectional lasing in a single mode laser.« less

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is basedmore » on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan{sup ©}600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.« less

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

PubMed Central

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Niu, Tianye; Zhu, Lei

2016-01-01

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan©600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan©600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution. PMID:27147376

Full waveform inversion using envelope-based global correlation norm

NASA Astrophysics Data System (ADS)

Oh, Ju-Won; Alkhalifah, Tariq

2018-05-01

To increase the feasibility of full waveform inversion on real data, we suggest a new objective function, which is defined as the global correlation of the envelopes of modelled and observed data. The envelope-based global correlation norm has the advantage of the envelope inversion that generates artificial low-frequency information, which provides the possibility to recover long-wavelength structure in an early stage. In addition, the envelope-based global correlation norm maintains the advantage of the global correlation norm, which reduces the sensitivity of the misfit to amplitude errors so that the performance of inversion on real data can be enhanced when the exact source wavelet is not available and more complex physics are ignored. Through the synthetic example for 2-D SEG/EAGE overthrust model with inaccurate source wavelet, we compare the performance of four different approaches, which are the least-squares waveform inversion, least-squares envelope inversion, global correlation norm and envelope-based global correlation norm. Finally, we apply the envelope-based global correlation norm on the 3-D Ocean Bottom Cable (OBC) data from the North Sea. The envelope-based global correlation norm captures the strong reflections from the high-velocity caprock and generates artificial low-frequency reflection energy that helps us recover long-wavelength structure of the model domain in the early stages. From this long-wavelength model, the conventional global correlation norm is sequentially applied to invert for higher-resolution features of the model.

Validating the shortened Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-55) in a sample of children with drug-resistant epilepsy.

PubMed

Conway, Lauryn; Widjaja, Elysa; Smith, Mary Lou; Speechley, Kathy N; Ferro, Mark A

2017-04-01

The aim of this study was to validate the newly developed shortened Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-55) in a sample of children with drug-resistant epilepsy. Data came from 136 children enrolled in the Impact of Pediatric Epilepsy Surgery on Health-Related Quality of Life Study (PEPSQOL), a multicenter prospective cohort study. Confirmatory factor analysis was used to assess the higher-order factor structure of the QOLCE-55. Convergent and divergent validity was assessed by correlating subscales of the KIDSCREEN-27 with the QOLCE-55. Measurement equivalence of the QOLCE-55 was evaluated using multiple-group confirmatory factor analysis of children with drug-resistant epilepsy from PEPSQOL versus children with new-onset epilepsy from HERQULES (Health-Related Quality of Life in Children with Epilepsy Study). The higher-order factor structure of the QOLCE-55 demonstrated adequate fit: Comparative Fit Index (CFI) = 0.948; Tucker-Lewis Index (TLI) = 0.946; Root Mean Square of Approximation (RMSEA) = 0.060 (90% confidence interval [CI] 0.054-0.065); Weighted Root Mean Square Residuals (WRMR) = 1.247. Higher-order factor loadings were strong, ranging from λ = 0.74 to 0.81. Internal consistency reliability was excellent (α = 0.97, subscales α > 0.82). QOLCE-55 subscales demonstrated moderate to strong correlations with similar subscales of the KIDSCREEN-27 (ρ = 0.43-0.75) and weak to moderate correlations with dissimilar subscales (ρ = 0.25-0.42). The QOLCE-55 demonstrated partial measurement equivalence at the level of strict invariance - χ 2 (2,823) = 3,727.9, CFI = 0.961, TLI = 0.962, RMSEA = 0.049 (0.044, 0.053), WRMR = 1.834. The findings provide support for the factor structure of the QOLCE-55 and contribute to its robust psychometric profile as a reliable and valid measure. Researchers and health practitioners should consider the QOLCE-55 as a viable option for reducing respondent burden when assessing health-related quality of life in children with epilepsy. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Prediction of STN-DBS Electrode Implantation Track in Parkinson's Disease by Using Local Field Potentials

PubMed Central

Telkes, Ilknur; Jimenez-Shahed, Joohi; Viswanathan, Ashwin; Abosch, Aviva; Ince, Nuri F.

2016-01-01

Optimal electrophysiological placement of the DBS electrode may lead to better long term clinical outcomes. Inter-subject anatomical variability and limitations in stereotaxic neuroimaging increase the complexity of physiological mapping performed in the operating room. Microelectrode single unit neuronal recording remains the most common intraoperative mapping technique, but requires significant expertise and is fraught by potential technical difficulties including robust measurement of the signal. In contrast, local field potentials (LFPs), owing to their oscillatory and robust nature and being more correlated with the disease symptoms, can overcome these technical issues. Therefore, we hypothesized that multiple spectral features extracted from microelectrode-recorded LFPs could be used to automate the identification of the optimal track and the STN localization. In this regard, we recorded LFPs from microelectrodes in three tracks from 22 patients during DBS electrode implantation surgery at different depths and aimed to predict the track selected by the neurosurgeon based on the interpretation of single unit recordings. A least mean square (LMS) algorithm was used to de-correlate LFPs in each track, in order to remove common activity between channels and increase their spatial specificity. Subband power in the beta band (11–32 Hz) and high frequency range (200–450 Hz) were extracted from the de-correlated LFP data and used as features. A linear discriminant analysis (LDA) method was applied both for the localization of the dorsal border of STN and the prediction of the optimal track. By fusing the information from these low and high frequency bands, the dorsal border of STN was localized with a root mean square (RMS) error of 1.22 mm. The prediction accuracy for the optimal track was 80%. Individual beta band (11–32 Hz) and the range of high frequency oscillations (200–450 Hz) provided prediction accuracies of 72 and 68% respectively. The best prediction result obtained with monopolar LFP data was 68%. These results establish the initial evidence that LFPs can be strategically fused with computational intelligence in the operating room for STN localization and the selection of the track for chronic DBS electrode implantation. PMID:27242404

The validity and reliability of the four square step test in different adult populations: a systematic review.

PubMed

Moore, Martha; Barker, Karen

2017-09-11

The four square step test (FSST) was first validated in healthy older adults to provide a measure of dynamic standing balance and mobility. The FSST has since been used in a variety of patient populations. The purpose of this systematic review is to determine the validity and reliability of the FSST in these different adult patient populations. The literature search was conducted to highlight all the studies that measured validity and reliability of the FSST. Six electronic databases were searched including AMED, CINAHL, MEDLINE, PEDro, Web of Science and Google Scholar. Grey literature was also searched for any documents relevant to the review. Two independent reviewers carried out study selection and quality assessment. The methodological quality was assessed using the QUADAS-2 tool, which is a validated tool for the quality assessment of diagnostic accuracy studies, and the COSMIN four-point checklist, which contains standards for evaluating reliability studies on the measurement properties of health instruments. Fifteen studies were reviewed studying community-dwelling older adults, Parkinson's disease, Huntington's disease, multiple sclerosis, vestibular disorders, post stroke, post unilateral transtibial amputation, knee pain and hip osteoarthritis. Three of the studies were of moderate methodological quality scoring low in risk of bias and applicability for all domains in the QUADAS-2 tool. Three studies scored "fair" on the COSMIN four-point checklist for the reliability components. The concurrent validity of the FSST was measured in nine of the studies with moderate to strong correlations being found. Excellent Intraclass Correlation Coefficients were found between physiotherapists carrying out the tests (ICC = .99) with good to excellent test-retest reliability shown in nine of the studies (ICC = .73-.98). The FSST may be an effective and valid tool for measuring dynamic balance and a participants' falls risk. It has been shown to have strong correlations with other measures of balance and mobility with good reliability shown in a number of populations. However, the quality of the papers reviewed was variable with key factors, such as sample size and test set up, needing to be addressed before the tool can be confidently used in these specified populations.

Different polarization dynamic states in a vector Yb-doped fiber laser.

PubMed

Li, Xingliang; Zhang, Shumin; Han, Huiyun; Han, Mengmeng; Zhang, Huaxing; Zhao, Luming; Wen, Fang; Yang, Zhenjun

2015-04-20

Different polarization dynamic states in an unidirectional, vector, Yb-doped fiber ring laser have been observed. A rich variety of dynamic states, including group velocity locked polarization domains and their splitting into regularly distributed multiple domains, polarization locked square pulses and their harmonic mode locking counterparts, and dissipative soliton resonances have all been observed with different operating parameters. We have also shown experimentally details of the conditions under which polarization-domain-wall dark pulses and bright square pulses form.

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Least Squares Moving-Window Spectral Analysis.

PubMed

Lee, Young Jong

2017-08-01

Least squares regression is proposed as a moving-windows method for analysis of a series of spectra acquired as a function of external perturbation. The least squares moving-window (LSMW) method can be considered an extended form of the Savitzky-Golay differentiation for nonuniform perturbation spacing. LSMW is characterized in terms of moving-window size, perturbation spacing type, and intensity noise. Simulation results from LSMW are compared with results from other numerical differentiation methods, such as single-interval differentiation, autocorrelation moving-window, and perturbation correlation moving-window methods. It is demonstrated that this simple LSMW method can be useful for quantitative analysis of nonuniformly spaced spectral data with high frequency noise.

Anisotropic mean-square displacements in two-dimensional colloidal crystals of tilted dipoles

NASA Astrophysics Data System (ADS)

Froltsov, V. A.; Likos, C. N.; Löwen, H.; Eisenmann, C.; Gasser, U.; Keim, P.; Maret, G.

2005-03-01

Superparamagnetic colloidal particles confined to a flat horizontal air-water interface in an external magnetic field, which is tilted relative to the interface, form anisotropic two-dimensional crystals resulting from their mutual dipole-dipole interactions. Using real-space experiments and harmonic lattice theory we explore the mean-square displacements of the particles in the directions parallel and perpendicular to the in-plane component of the external magnetic field as a function of the tilt angle. We find that the anisotropy of the mean-square displacement behaves nonmonotonically as a function of the tilt angle and does not correlate with the structural anisotropy of the crystal.

Scaling a Conditional Proximity Matrix to Symmetry.

ERIC Educational Resources Information Center

Levin, Joseph; Brown, Morton

1979-01-01

Two least squares procedures for symmetrization of a conditional proximity matrix are derived. The solutions provide multiplicative constants for scaling the rows or columns of the matrix to maximize symmetry. (Author/JKS)

Mathematical Investigations Using Logo. Part Two.

ERIC Educational Resources Information Center

Brown, Ken

1986-01-01

Programs (using Logo) developed by children to produce multiples, the Fibonacci series, and square numbers are presented, with graphical representations of functions introduced. Another investigation involves drawing a circle using turtle graphics. (MNS)

Weighted regression analysis and interval estimators

Treesearch

Donald W. Seegrist

1974-01-01

A method for deriving the weighted least squares estimators for the parameters of a multiple regression model. Confidence intervals for expected values, and prediction intervals for the means of future samples are given.

Examination of Parameters Affecting the House Prices by Multiple Regression Analysis and its Contributions to Earthquake-Based Urban Transformation

NASA Astrophysics Data System (ADS)

Denli, H. H.; Durmus, B.

2016-12-01

The purpose of this study is to examine the factors which may affect the apartment prices with multiple linear regression analysis models and visualize the results by value maps. The study is focused on a county of Istanbul - Turkey. Totally 390 apartments around the county Umraniye are evaluated due to their physical and locational conditions. The identification of factors affecting the price of apartments in the county with a population of approximately 600k is expected to provide a significant contribution to the apartment market.Physical factors are selected as the age, number of rooms, size, floor numbers of the building and the floor that the apartment is positioned in. Positional factors are selected as the distances to the nearest hospital, school, park and police station. Totally ten physical and locational parameters are examined by regression analysis.After the regression analysis has been performed, value maps are composed from the parameters age, price and price per square meters. The most significant of the composed maps is the price per square meters map. Results show that the location of the apartment has the most influence to the square meter price information of the apartment. A different practice is developed from the composed maps by searching the ability of using price per square meters map in urban transformation practices. By marking the buildings older than 15 years in the price per square meters map, a different and new interpretation has been made to determine the buildings, to which should be given priority during an urban transformation in the county.This county is very close to the North Anatolian Fault zone and is under the threat of earthquakes. By marking the apartments older than 15 years on the price per square meters map, both older and expensive square meters apartments list can be gathered. By the help of this list, the priority could be given to the selected higher valued old apartments to support the economy of the country during an earthquake loss. We may call this urban transformation as earthquake-based urban transformation.

Multifrequency synthesis and extraction using square wave projection patterns for quantitative tissue imaging.

PubMed

Nadeau, Kyle P; Rice, Tyler B; Durkin, Anthony J; Tromberg, Bruce J

2015-11-01

We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI.

Multifrequency synthesis and extraction using square wave projection patterns for quantitative tissue imaging

PubMed Central

Nadeau, Kyle P.; Rice, Tyler B.; Durkin, Anthony J.; Tromberg, Bruce J.

2015-01-01

Abstract. We present a method for spatial frequency domain data acquisition utilizing a multifrequency synthesis and extraction (MSE) method and binary square wave projection patterns. By illuminating a sample with square wave patterns, multiple spatial frequency components are simultaneously attenuated and can be extracted to determine optical property and depth information. Additionally, binary patterns are projected faster than sinusoids typically used in spatial frequency domain imaging (SFDI), allowing for short (millisecond or less) camera exposure times, and data acquisition speeds an order of magnitude or more greater than conventional SFDI. In cases where sensitivity to superficial layers or scattering is important, the fundamental component from higher frequency square wave patterns can be used. When probing deeper layers, the fundamental and harmonic components from lower frequency square wave patterns can be used. We compared optical property and depth penetration results extracted using square waves to those obtained using sinusoidal patterns on an in vivo human forearm and absorbing tube phantom, respectively. Absorption and reduced scattering coefficient values agree with conventional SFDI to within 1% using both high frequency (fundamental) and low frequency (fundamental and harmonic) spatial frequencies. Depth penetration reflectance values also agree to within 1% of conventional SFDI. PMID:26524682

Cubic law with aperture-length correlation: implications for network scale fluid flow

NASA Astrophysics Data System (ADS)

Klimczak, Christian; Schultz, Richard A.; Parashar, Rishi; Reeves, Donald M.

2010-06-01

Previous studies have computed and modeled fluid flow through fractured rock with the parallel plate approach where the volumetric flow per unit width normal to the direction of flow is proportional to the cubed aperture between the plates, referred to as the traditional cubic law. When combined with the square root relationship of displacement to length scaling of opening-mode fractures, total flow rates through natural opening-mode fractures are found to be proportional to apertures to the fifth power. This new relationship was explored by examining a suite of flow simulations through fracture networks using the discrete fracture network model (DFN). Flow was modeled through fracture networks with the same spatial distribution of fractures for both correlated and uncorrelated fracture length-to-aperture relationships. Results indicate that flow rates are significantly higher for correlated DFNs. Furthermore, the length-to-aperture relations lead to power-law distributions of network hydraulic conductivity which greatly influence equivalent permeability tensor values. These results confirm the importance of the correlated square root relationship of displacement to length scaling for total flow through natural opening-mode fractures and, hence, emphasize the role of these correlations for flow modeling.

Diffuse correlation tomography in the transport regime: A theoretical study of the sensitivity to Brownian motion.

PubMed

Tricoli, Ugo; Macdonald, Callum M; Durduran, Turgut; Da Silva, Anabela; Markel, Vadim A

2018-02-01

Diffuse correlation tomography (DCT) uses the electric-field temporal autocorrelation function to measure the mean-square displacement of light-scattering particles in a turbid medium over a given exposure time. The movement of blood particles is here estimated through a Brownian-motion-like model in contrast to ordered motion as in blood flow. The sensitivity kernel relating the measurable field correlation function to the mean-square displacement of the particles can be derived by applying a perturbative analysis to the correlation transport equation (CTE). We derive an analytical expression for the CTE sensitivity kernel in terms of the Green's function of the radiative transport equation, which describes the propagation of the intensity. We then evaluate the kernel numerically. The simulations demonstrate that, in the transport regime, the sensitivity kernel provides sharper spatial information about the medium as compared with the correlation diffusion approximation. Also, the use of the CTE allows one to explore some additional degrees of freedom in the data such as the collimation direction of sources and detectors. Our results can be used to improve the spatial resolution of DCT, in particular, with applications to blood flow imaging in regions where the Brownian motion is dominant.

Diffuse correlation tomography in the transport regime: A theoretical study of the sensitivity to Brownian motion

NASA Astrophysics Data System (ADS)

Tricoli, Ugo; Macdonald, Callum M.; Durduran, Turgut; Da Silva, Anabela; Markel, Vadim A.

2018-02-01

Diffuse correlation tomography (DCT) uses the electric-field temporal autocorrelation function to measure the mean-square displacement of light-scattering particles in a turbid medium over a given exposure time. The movement of blood particles is here estimated through a Brownian-motion-like model in contrast to ordered motion as in blood flow. The sensitivity kernel relating the measurable field correlation function to the mean-square displacement of the particles can be derived by applying a perturbative analysis to the correlation transport equation (CTE). We derive an analytical expression for the CTE sensitivity kernel in terms of the Green's function of the radiative transport equation, which describes the propagation of the intensity. We then evaluate the kernel numerically. The simulations demonstrate that, in the transport regime, the sensitivity kernel provides sharper spatial information about the medium as compared with the correlation diffusion approximation. Also, the use of the CTE allows one to explore some additional degrees of freedom in the data such as the collimation direction of sources and detectors. Our results can be used to improve the spatial resolution of DCT, in particular, with applications to blood flow imaging in regions where the Brownian motion is dominant.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fundamental Analysis of the Linear Multiple Regression Technique for Quantification of Water Quality Parameters from Remote Sensing Data. Ph.D. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Whitlock, C. H., III

1977-01-01

Constituents with linear radiance gradients with concentration may be quantified from signals which contain nonlinear atmospheric and surface reflection effects for both homogeneous and non-homogeneous water bodies provided accurate data can be obtained and nonlinearities are constant with wavelength. Statistical parameters must be used which give an indication of bias as well as total squared error to insure that an equation with an optimum combination of bands is selected. It is concluded that the effect of error in upwelled radiance measurements is to reduce the accuracy of the least square fitting process and to increase the number of points required to obtain a satisfactory fit. The problem of obtaining a multiple regression equation that is extremely sensitive to error is discussed.

Square-antiprismatic eight-coordinate complexes of divalent first-row transition metal cations: a density functional theory exploration of the electronic-structural landscape.

PubMed

Conradie, Jeanet; Patra, Ashis K; Harrop, Todd C; Ghosh, Abhik

2015-02-16

Density functional theory (in the form of the PW91, BP86, OLYP, and B3LYP exchange-correlation functionals) has been used to map out the low-energy states of a series of eight-coordinate square-antiprismatic (D2d) first-row transition metal complexes, involving Mn(II), Fe(II), Co(II), Ni(II), and Cu(II), along with a pair of tetradentate N4 ligands. Of the five complexes, the Mn(II) and Fe(II) complexes have been synthesized and characterized structurally and spectroscopically, whereas the other three are as yet unknown. Each N4 ligand consists of a pair of terminal imidazole units linked by an o-phenylenediimine unit. The imidazole units are the strongest ligands in these complexes and dictate the spatial disposition of the metal three-dimensional orbitals. Thus, the dx(2)-y(2) orbital, whose lobes point directly at the coordinating imidazole nitrogens, has the highest orbital energy among the five d orbitals, whereas the dxy orbital has the lowest orbital energy. In general, the following orbital ordering (in order of increasing orbital energy) was found to be operative: dxy < dxz = dyz ≤ dz(2) < dx(2)-y(2). The square-antiprism geometry does not lead to large energy gaps between the d orbitals, which leads to an S = 2 ground state for the Fe(II) complex. Nevertheless, the dxy orbital has significantly lower energy relative to that of the dxz and dyz orbitals. Accordingly, the ground state of the Fe(II) complex corresponds unambiguously to a dxy(2)dxz(1)dyz(1)dz(2)(1)dx(2)-y(2)(1) electronic configuration. Unsurprisingly, the Mn(II) complex has an S = 5/2 ground state and no low-energy d-d excited states within 1.0 eV of the ground state. The Co(II) complex, on the other hand, has both a low-lying S = 1/2 state and multiple low-energy S = 3/2 states. Very long metal-nitrogen bonds are predicted for the Ni(II) and Cu(II) complexes; these bonds may be too fragile to survive in solution or in the solid state, and the complexes may therefore not be isolable. Overall, the different exchange-correlation functionals provided a qualitatively consistent and plausible picture of the low-energy d-d excited states of the complexes.

Certification in Structural Health Monitoring Systems

DTIC Science & Technology

2011-09-01

validation [3,8]. This may be accomplished by computing the sum of squares of pure error ( SSPE ) and its associated squared correlation [3,8]. To compute...these values, a cross- validation sample must be established. In general, if the SSPE is high, the model does not predict well on independent data...plethora of cross- validation methods, some of which are more useful for certain models than others [3,8]. When possible, a disclosure of the SSPE

Experimental evidence for bounds on quantum correlations.

PubMed

Bovino, F A; Castagnoli, G; Degiovanni, I P; Castelletto, S

2004-02-13

We implemented the experiment proposed by Cabello in the preceding Letter to test the bounds of quantum correlation. As expected from the theory we found that, for certain choices of local observables, Tsirelson's bound of the Clauser-Horne-Shimony-Holt inequality (2 x square root of 2) is not reached by any quantum states.

[The research on separating and extracting overlapping spectral feature lines in LIBS using damped least squares method].

PubMed

Wang, Yin; Zhao, Nan-jing; Liu, Wen-qing; Yu, Yang; Fang, Li; Meng, De-shuo; Hu, Li; Zhang, Da-hai; Ma, Min-jun; Xiao, Xue; Wang, Yu; Liu, Jian-guo

2015-02-01

In recent years, the technology of laser induced breakdown spectroscopy has been developed rapidly. As one kind of new material composition detection technology, laser induced breakdown spectroscopy can simultaneously detect multi elements fast and simply without any complex sample preparation and realize field, in-situ material composition detection of the sample to be tested. This kind of technology is very promising in many fields. It is very important to separate, fit and extract spectral feature lines in laser induced breakdown spectroscopy, which is the cornerstone of spectral feature recognition and subsequent elements concentrations inversion research. In order to realize effective separation, fitting and extraction of spectral feature lines in laser induced breakdown spectroscopy, the original parameters for spectral lines fitting before iteration were analyzed and determined. The spectral feature line of' chromium (Cr I : 427.480 nm) in fly ash gathered from a coal-fired power station, which was overlapped with another line(FeI: 427.176 nm), was separated from the other one and extracted by using damped least squares method. Based on Gauss-Newton iteration, damped least squares method adds damping factor to step and adjust step length dynamically according to the feedback information after each iteration, in order to prevent the iteration from diverging and make sure that the iteration could converge fast. Damped least squares method helps to obtain better results of separating, fitting and extracting spectral feature lines and give more accurate intensity values of these spectral feature lines: The spectral feature lines of chromium in samples which contain different concentrations of chromium were separated and extracted. And then, the intensity values of corresponding spectral lines were given by using damped least squares method and least squares method separately. The calibration curves were plotted, which showed the relationship between spectral line intensity values and chromium concentrations in different samples. And then their respective linear correlations were compared. The experimental results showed that the linear correlation of the intensity values of spectral feature lines and the concentrations of chromium in different samples, which was obtained by damped least squares method, was better than that one obtained by least squares method. And therefore, damped least squares method was stable, reliable and suitable for separating, fitting and extracting spectral feature lines in laser induced breakdown spectroscopy.

Relationships of the phase velocity with the microarchitectural parameters in bovine trabecular bone in vitro: Application of a stratified model

NASA Astrophysics Data System (ADS)

Lee, Kang Il

2012-08-01

The present study aims to provide insight into the relationships of the phase velocity with the microarchitectural parameters in bovine trabecular bone in vitro. The frequency-dependent phase velocity was measured in 22 bovine femoral trabecular bone samples by using a pair of transducers with a diameter of 25.4 mm and a center frequency of 0.5 MHz. The phase velocity exhibited positive correlation coefficients of 0.48 and 0.32 with the ratio of bone volume to total volume and the trabecular thickness, respectively, but a negative correlation coefficient of -0.62 with the trabecular separation. The best univariate predictor of the phase velocity was the trabecular separation, yielding an adjusted squared correlation coefficient of 0.36. The multivariate regression models yielded adjusted squared correlation coefficients of 0.21-0.36. The theoretical phase velocity predicted by using a stratified model for wave propagation in periodically stratified media consisting of alternating parallel solid-fluid layers showed reasonable agreements with the experimental measurements.

Measuring patchy reionization with kSZ2-21 cm correlations

NASA Astrophysics Data System (ADS)

Ma, Q.; Helgason, K.; Komatsu, E.; Ciardi, B.; Ferrara, A.

2018-05-01

We study cross-correlations of the kinetic Sunyaev-Zel'dovich effect (kSZ) and 21 cm signals during the epoch of reionization (EoR) to measure the effects of patchy reionisation. Since the kSZ effect is proportional to the line-of-sight velocity, the kSZ-21 cm cross correlation suffers from cancellation at small angular scales. We thus focus on the correlation between the kSZ-squared field (kSZ2) and 21 cm signals. When the global ionization fraction is low (xe ≲ 0.7), the kSZ2 fluctuation is dominated by rare ionized bubbles, which leads to an anticorrelation with the 21 cm signal. When 0.8 ≲ xe < 1, the correlation is dominated by small pockets of neutral regions, leading to a positive correlation. However, at very high redshifts when xe < 0.15, the spin temperature fluctuations change the sign of the correlation from negative to positive, as weakly ionized regions can have strong 21 cm signals in this case. To extract this correlation, we find that Wiener filtering is effective in removing large signals from the primary cosmic microwave background (CMB) anisotropy. The expected signal-to-noise ratios for a ˜10-h integration of upcoming Square Kilometre Array data cross-correlated with maps from the current generation of CMB observatories with 3.4μK arcmin noise and 1.7 arcmin beam over 100 deg2 are 51, 60, and 37 for xe = 0.2, 0.5, and 0.9, respectively.

The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

ERIC Educational Resources Information Center

Le, Huy; Marcus, Justin

2012-01-01

This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

Blind Equalization and Fading Channel Signal Recovery of OFDM Modulation

DTIC Science & Technology

2011-03-01

Square LTI Linear Time Invariant MIMO Multiple-Input Multiple-Output OFDM Orthogonal Frequency-Division Multiplexing QPSK Quadrature Phase-Shift...AND FADING CHANNEL SIGNAL RECOVERY OF OFDM MODULATION by Anthony G. Stranges March 2011 Thesis Co-Advisors: Roberto Cristi Frank Kragh...Master’s Thesis 4. TITLE AND SUBTITLE Blind Equalization and Fading Channel Signal Recovery of OFDM Modulation 6. AUTHOR(S) Anthony G. Stranges

Modeling The Skeleton Weight of an Adult Caucasian Man.

PubMed

Avtandilashvili, Maia; Tolmachev, Sergei Y

2018-05-17

The reference value for the skeleton weight of an adult male (10.5 kg) recommended by the International Commission on Radiological Protection in Publication 70 is based on weights of dissected skeletons from 44 individuals, including two U.S. Transuranium and Uranium Registries whole-body donors. The International Commission on Radiological Protection analysis of anatomical data from 31 individuals with known values of body height demonstrated significant correlation between skeleton weight and body height. The corresponding regression equation, Wskel (kg) = -10.7 + 0.119 × H (cm), published in International Commission on Radiological Protection Publication 70 is typically used to estimate the skeleton weight from body height. Currently, the U.S. Transuranium and Uranium Registries holds data on individual bone weights from a total of 40 male whole-body donors, which has provided a unique opportunity to update the International Commission on Radiological Protection skeleton weight vs. body height equation. The original International Commission on Radiological Protection Publication 70 and the new U.S. Transuranium and Uranium Registries data were combined in a set of 69 data points representing a group of 33- to 95-y-old individuals with body heights and skeleton weights ranging from 155 to 188 cm and 6.5 to 13.4 kg, respectively. Data were fitted with a linear least-squares regression. A significant correlation between the two parameters was observed (r = 0.28), and an updated skeleton weight vs. body height equation was derived: Wskel (kg) = -6.5 + 0.093 × H (cm). In addition, a correlation of skeleton weight with multiple variables including body height, body weight, and age was evaluated using multiple regression analysis, and a corresponding fit equation was derived: Wskel (kg) = -0.25 + 0.046 × H (cm) + 0.036 × Wbody (kg) - 0.012 × A (y). These equations will be used to estimate skeleton weights and, ultimately, total skeletal actinide activities for biokinetic modeling of U.S. Transuranium and Uranium Registries partial-body donation cases.

Changes and correlates in multiple sexual partnerships among Chinese adult women--population-based surveys in 2000 and 2006.

PubMed

Yingying, Huang; Smith, Kumi; Suiming, Pan

2011-06-01

The sexual transmission of HIV and STI is becoming a major public health concern in China. However, studies on sexuality in China remain scant, particularly those that analyze female sexuality. This study is to investigate the prevalence of multiple sexual partnerships (MSP) among adult women, and to examine trends and correlates for having more than one lifetime sexual partner. MSP, coded as having one or none vs. two or more lifetime sexual partners, was the key binary outcome measure. The data were from two national probability surveys on sexual behaviors in China carried out in 2000 and 2006. The sample size of adult women was 1899 in 2000 (total sample n=3812), and 2626 in 2006 (n=5404). Overall prevalence of MSP increased from 8.1% in 2000 to 29.6% in 2006 (chi-square test, significance = 0.000). The most rapid changes took place among women with less education, those who worked in blue-collar jobs and lower social-status positions, and those living in rural areas or small towns. Women who were better educated, lived in big cities, and held management-level occupations exhibited less change but had a higher baselines prevalence of MSP, suggesting that changes in MSP behavior may occur initially among women of higher socioeconomic status. Based on the 2006 data-set, significant positive correlates of MSP included more years of education, being in a long-term relationship, being middle aged, having a lower-status job, going out dancing at entertainments venues, and being a state of overall health in the past 12 months. The significant recent increase in MSP among women reinforces the need to examine China's sexual revolution in the context of a rapidly transitioning society. Findings regarding female sexuality also raise new questions to be explored in further sexuality studies, in order to better understand population sexual behaviors and to inform future HIV-prevention efforts.

[Identification of Dendrobium varieties by Fourier transform infrared spectroscopy combined with spectral retrieval].

PubMed

Liu, Fei; Wang, Yuan-zhong; Deng, Xing-yan; Jin, Hang; Yang, Chun-yan

2014-06-01

The infrared spectral of stems of 165 trees of 23 Dendrobium varieties were obtained by means of Fourier transform infrared spectroscopy technique. The spectra show that the spectra of all the samples were similar, and the main components of stem of Dendrobium is cellulose. By the spectral professional software Omnic8.0, three spectral databases were constructed. Lib01 includes of the average spectral of the first four trees of every variety, while Lib02 and Lib03 are constructed from the first-derivative spectra and the second-derivative spectra of average spectra, separately. The correlation search, the square difference retrieval and the square differential difference retrieval of the spectra are performed with the spectral database Lib01 in the specified range of 1 800-500 cm(-1), and the yield correct rate of 92.7%, 74.5% and 92.7%, respectively. The square differential difference retrieval of the first-derivative spectra and the second-derivative spectra is carried out with Lib02 and Lib03 in the same specified range 1 800-500 cm(-1), and shows correct rate of 93.9% for the former and 90.3% for the later. The results show that the first-derivative spectral retrieval of square differential difference algorithm is more suitabe for discerning Dendrobium varieties, and FTIR combining with the spectral retrieval method can identify different varieties of Dendrobium, and the correlation retrieval, the square differential retrieval, the first-derivative spectra and second-derivative spectra retrieval in the specified spectral range are effective and simple way of distinguishing different varieties of Dendrobium.

[Near infrared spectroscopy study on water content in turbine oil].

PubMed

Chen, Bin; Liu, Ge; Zhang, Xian-Ming

2013-11-01

Near infrared (NIR) spectroscopy combined with successive projections algorithm (SPA) was investigated for determination of water content in turbine oil. Through the 57 samples of different water content in turbine oil scanned applying near infrared (NIR) spectroscopy, with the water content in the turbine oil of 0-0.156%, different pretreatment methods such as the original spectra, first derivative spectra and differential polynomial least squares fitting algorithm Savitzky-Golay (SG), and successive projections algorithm (SPA) were applied for the extraction of effective wavelengths, the correlation coefficient (R) and root mean square error (RMSE) were used as the model evaluation indices, accordingly water content in turbine oil was investigated. The results indicated that the original spectra with different water content in turbine oil were pretreated by the performance of first derivative + SG pretreatments, then the selected effective wavelengths were used as the inputs of least square support vector machine (LS-SVM). A total of 16 variables selected by SPA were employed to construct the model of SPA and least square support vector machine (SPA-LS-SVM). There is 9 as The correlation coefficient was 0.975 9 and the root of mean square error of validation set was 2.655 8 x 10(-3) using the model, and it is feasible to determine the water content in oil using near infrared spectroscopy and SPA-LS-SVM, and an excellent prediction precision was obtained. This study supplied a new and alternative approach to the further application of near infrared spectroscopy in on-line monitoring of contamination such as water content in oil.

The Impact of Body Mass Index on Heterotopic Ossification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mourad, Waleed Fouad, E-mail: Waleed246@gmail.com; Department of Radiation Oncology, Beth Israel Medical Center, New York, NY; Department of Radiation Oncology, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY

2012-04-01

Purpose: To analyze the impact of different body mass index (BMI) as a surrogate marker for heterotopic ossification (HO) in patients who underwent surgical repair (SR) for displaced acetabular fractures (DAF) followed by radiation therapy (RT). Methods and Materials: This is a single-institution retrospective study of 395 patients. All patients underwent SR for DAF followed by RT {+-} indomethacin. All patients received postoperative RT, 7 Gy, within 72 h. The patients were separated into four groups based on their BMI: <18.5, 18.5-24.9, 25-29.9, and >30. The end point of this study was to evaluate the efficacy of RT {+-} indomethacinmore » in preventing HO in patients with different BMI. Results: Analysis of BMI showed an increasing incidence of HO with increasing BMI: <18.5, (0%) 0/6 patients; 18.5-24.9 (6%), 6 of 105 patients developed HO; 25-29.9 (19%), 22 of 117; >30 (31%), 51 of 167. Chi-square and multivariate logistic regression analysis showed that the correlation between odds of HO and BMI is significant, p < 0.0001. As the BMI increased, the risk of HO and Brooker Classes 3, 4 HO increased. The risk of developing HO is 1.0 Multiplication-Sign (10%) more likely among those with higher BMI compared with those with lower BMI. For a one-unit increase in BMI the log odds of HO increases by 1.0, 95% CI (1.06-1.14). Chi-square test shows no significant difference among all other factors and HO (e.g., indomethacin, race, gender). Conclusions: Despite similar surgical treatment and prophylactic measures (RT {+-} indomethacin), the risk of HO appears to significantly increase in patients with higher BMI after DAF. Higher single-fraction doses or multiple fractions and/or combination therapy with nonsteroidal inflammatory drugs may be of greater benefit to these patients.« less

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.

2013-01-01

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

Combined Synchrotron X-ray Diffraction and Digital Image Correlation Technique for Measurement of Austenite Transformation with Strain in TRIP-assisted Steels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poling, Whitney A.; Savic, Vesna; Hector, Louis G.

2016-04-05

The strain-induced, diffusionless shear transformation of retained austenite to martensite during straining of transformation induced plasticity (TRIP) assisted steels increases strain hardening and delays necking and fracture leading to exceptional ductility and strength, which are attractive for automotive applications. A novel technique that provides the retained austenite volume fraction variation with strain in TRIP-assisted steels with improved precision is presented. Digital images of the gauge section of tensile specimens were first recorded up to selected plastic strains with a stereo digital image correlation (DIC) system. The austenite volume fraction was measured by synchrotron X-ray diffraction from small squares cut frommore » the gage section. Strain fields in the squares were then computed by localizing the strain measurement to the corresponding region of a given square during DIC post-processing of the images recorded during tensile testing. Results obtained for a QP980 steel are used to study the influence of initial volume fraction of austenite and the austenite transformation with strain on tensile mechanical behavior.« less

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

PubMed

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

PubMed Central

Yang, Yingbao; Li, Xiaolong; Pan, Xin; Zhang, Yong; Cao, Chen

2017-01-01

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. PMID:28368301

TOPMODEL simulations of streamflow and depth to water table in Fishing Brook Watershed, New York, 2007-09

USGS Publications Warehouse

Nystrom, Elizabeth A.; Burns, Douglas A.

2011-01-01

TOPMODEL uses a topographic wetness index computed from surface-elevation data to simulate streamflow and subsurface-saturation state, represented by the saturation deficit. Depth to water table was computed from simulated saturation-deficit values using computed soil properties. In the Fishing Brook Watershed, TOPMODEL was calibrated to the natural logarithm of streamflow at the study area outlet and depth to water table at Sixmile Wetland using a combined multiple-objective function. Runoff and depth to water table responded differently to some of the model parameters, and the combined multiple-objective function balanced the goodness-of-fit of the model realizations with respect to these parameters. Results show that TOPMODEL reasonably simulated runoff and depth to water table during the study period. The simulated runoff had a Nash-Sutcliffe efficiency of 0.738, but the model underpredicted total runoff by 14 percent. Depth to water table computed from simulated saturation-deficit values matched observed water-table depth moderately well; the root mean squared error of absolute depth to water table was 91 millimeters (mm), compared to the mean observed depth to water table of 205 mm. The correlation coefficient for temporal depth-to-water-table fluctuations was 0.624. The variability of the TOPMODEL simulations was assessed using prediction intervals grouped using the combined multiple-objective function. The calibrated TOPMODEL results for the entire study area were applied to several subwatersheds within the study area using computed hydrogeomorphic properties of the subwatersheds.

Control over self-assembly of diblock copolymers on hexagonal and square templates for high area density circuit boards.

PubMed

Feng, Jie; Cavicchi, Kevin A; Heinz, Hendrik

2011-12-27

Self-assembled diblock copolymer melts on patterned substrates can induce a smaller characteristic domain spacing compared to predefined lithographic patterns and enable the manufacture of circuit boards with a high area density of computing and storage units. Monte Carlo simulation using coarse-grain models of polystyrene-b-polydimethylsiloxane shows that the generation of high-density hexagonal and square patterns is controlled by the ratio N(D) of the surface area per post and the surface area per spherical domain of neat block copolymer. N(D) represents the preferred number of block copolymer domains per post. Selected integer numbers support the formation of ordered structures on hexagonal (1, 3, 4, 7, 9) and square (1, 2, 5, 7) templates. On square templates, only smaller numbers of block copolymer domains per post support the formation of ordered arrays with significant stabilization energies relative to hexagonal morphology. Deviation from suitable integer numbers N(D) increases the likelihood of transitional morphologies between square and hexagonal. Upon increasing the spacing of posts on the substrate, square arrays, nested square arrays, and disordered hexagonal morphologies with multiple coordination numbers were identified, accompanied by a decrease in stabilization energy. Control over the main design parameter N(D) may allow an up to 7-fold increase in density of spherical block copolymer domains per surface area in comparison to the density of square posts and provide access to a wide range of high-density nanostructures to pattern electronic devices.

Description of the supporting factors of final project in Mathematics and Natural Sciences Faculty of Syiah Kuala University with multiple correspondence analysis

NASA Astrophysics Data System (ADS)

Rusyana, Asep; Nurhasanah; Maulizasari

2018-05-01

Syiah Kuala University (Unsyiah) is hoped to have graduates who are qualified for working or creating a field of work. A final project course implementation process must be effective. This research uses data from the evaluation conducted by Mathematics and Natural Sciences Faculty (FMIPA) of Unsyiah. Some of the factors that support the completion of the final project are duration, guidance, the final project seminars, facility, public impact, and quality. This research aims to know the factors that have a relationship with the completion of the final project and identify similarities among variables. The factors that support the completion of the final project at every study program in FMIPA are (1) duration, (2) guidance and (3) facilities. These factors are examined for the correlations by chi-square test. After that, the variables are analyzed with multiple correspondence analysis. Based on the plot of correspondence, the activities of the guidance and facilities in Informatics Study Program are included in the fair category, while the guidance and facilities in the Chemistry are included in the best category. Besides that, students in Physics can finish the final project with the fastest completion duration, while students in Pharmacy finish for the longest time.

Reliability and equivalence of alternate forms for the Symbol Digit Modalities Test: implications for multiple sclerosis clinical trials.

PubMed

Benedict, Ralph H B; Smerbeck, Audrey; Parikh, Rajavi; Rodgers, Jonathan; Cadavid, Diego; Erlanger, David

2012-09-01

Cognitive impairment is common in multiple sclerosis (MS), but is seldom assessed in clinical trials investigating the effects of disease-modifying therapies. The Symbol Digit Modalities Test (SDMT) is a particularly promising tool due to its sensitivity and robust correlation with brain magnetic resonance imaging (MRI) and vocational disability. Unfortunately, there are no validated alternate SDMT forms, which are needed to mitigate practice effects. The aim of the study was to assess the reliability and equivalence of SDMT alternate forms. Twenty-five healthy participants completed each of five alternate versions of the SDMT - the standard form, two versions from the Rao Brief Repeatable Battery, and two forms specifically designed for this study. Order effects were controlled using a Latin-square research design. All five versions of the SDMT produced mean values within 3 raw score points of one another. Three forms were very consistent, and not different by conservative statistical tests. The SDMT test-retest reliability using these forms was good to excellent, with all r values exceeding 0.80. For the first time, we find good evidence that at least three alternate versions of the SDMT are of equivalent difficulty in healthy adults. The forms are reliable, and can be implemented in clinical trials emphasizing cognitive outcomes.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran.

PubMed

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-04-01

Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people's general health. To determine marital satisfaction and its relationship with job stress and general health of nurses. This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses.

Spectroscopic sensitivity of real-time, rapidly induced phytochemical change in response to damage.

PubMed

Couture, John J; Serbin, Shawn P; Townsend, Philip A

2013-04-01

An ecological consequence of plant-herbivore interactions is the phytochemical induction of defenses in response to insect damage. Here, we used reflectance spectroscopy to characterize the foliar induction profile of cardenolides in Asclepias syriaca in response to damage, tracked in vivo changes and examined the influence of multiple plant traits on cardenolide concentrations. Foliar cardenolide concentrations were measured at specific time points following damage to capture their induction profile. Partial least-squares regression (PLSR) modeling was employed to calibrate cardenolide concentrations to reflectance spectroscopy. In addition, subsets of plants were either repeatedly sampled to track in vivo changes or modified to reduce latex flow to damaged areas. Cardenolide concentrations and the induction profile of A. syriaca were well predicted using models derived from reflectance spectroscopy, and this held true for repeatedly sampled plants. Correlations between cardenolides and other foliar-related variables were weak or not significant. Plant modification for latex reduction inhibited an induced cardenolide response. Our findings show that reflectance spectroscopy can characterize rapid phytochemical changes in vivo. We used reflectance spectroscopy to identify the mechanisms behind the production of plant secondary metabolites, simultaneously characterizing multiple foliar constituents. In this case, cardenolide induction appears to be largely driven by enhanced latex delivery to leaves following damage. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Red Wine Age Estimation by the Alteration of Its Color Parameters: Fourier Transform Infrared Spectroscopy as a Tool to Monitor Wine Maturation Time

PubMed Central

Basalekou, M.; Pappas, C.; Kotseridis, Y.; Tarantilis, P. A.; Kontaxakis, E.

2017-01-01

Color, phenolic content, and chemical age values of red wines made from Cretan grape varieties (Kotsifali, Mandilari) were evaluated over nine months of maturation in different containers for two vintages. The wines differed greatly on their anthocyanin profiles. Mid-IR spectra were also recorded with the use of a Fourier Transform Infrared Spectrophotometer in ZnSe disk mode. Analysis of Variance was used to explore the parameter's dependency on time. Determination models were developed for the chemical age indexes using Partial Least Squares (PLS) (TQ Analyst software) considering the spectral region 1830–1500 cm−1. The correlation coefficients (r) for chemical age index i were 0.86 for Kotsifali (Root Mean Square Error of Calibration (RMSEC) = 0.067, Root Mean Square Error of Prediction (RMSEP) = 0,115, and Root Mean Square Error of Validation (RMSECV) = 0.164) and 0.90 for Mandilari (RMSEC = 0.050, RMSEP = 0.040, and RMSECV = 0.089). For chemical age index ii the correlation coefficients (r) were 0.86 and 0.97 for Kotsifali (RMSEC 0.044, RMSEP = 0.087, and RMSECV = 0.214) and Mandilari (RMSEC = 0.024, RMSEP = 0.033, and RMSECV = 0.078), respectively. The proposed method is simpler, less time consuming, and more economical and does not require chemical reagents. PMID:29225994

The Shame and Guilt Scales of the Test of Self-Conscious Affect-Adolescent (TOSCA-A): Psychometric Properties for Responses from Children, and Measurement Invariance Across Children and Adolescents

PubMed Central

Watson, Shaun D.; Gomez, Rapson; Gullone, Eleonora

2016-01-01

This study examined various psychometric properties of the items comprising the shame and guilt scales of the Test of Self-Conscious Affect-Adolescent (TOSCA-A) in a group children between 8 and 11 years of age. A total of 699 children (367 females and 332 males) completed these scales, and also measures of depression and empathy. Confirmatory factor analysis (CFA) provided support for an oblique two-factor model, with the originally proposed shame and guilt items comprising shame and guilt factors, respectively. There was good internal consistency reliability for the shame and guilt scales, with omega coefficient values of 0.77 and 0.81 for shame and guilt, respectively. Also, shame correlated with depression symptoms positively (0.34, p < 0.001) and had no relation with empathy (-0.07, ns). Guilt correlated with depression symptoms negatively (-0.28, p < 0.001), and with empathy positively (0.13. p < 0.05). Thus there was support for the convergent and discriminant validity of the shame and guilt factors. Multiple-group CFA comparing this group of children with a separate group of adolescents (320 females and 242 males), based on the chi-square difference test, supported full metric invariance, the intercept invariance of 17 of the 30 shame and guilt items, and higher latent mean scores among children for both shame and guilt. The non-equivalency for intercepts and mean scores were of small effect sizes. Comparisons based on the difference in root mean squared error of approximation values supported full measurement invariance and no group difference for latent mean scores. The findings in the current study support the use of the TOSCA-A in children and the valid comparison of scores between children and adolescents, thereby opening up the possibility of evaluating change in the TOSCA-A shame and guilt factors over these developmental age groups. PMID:27242573

Phase transition in 2-d system of quadrupoles on square lattice with anisotropic field

NASA Astrophysics Data System (ADS)

Sallabi, A. K.; Alkhttab, M.

2014-12-01

Monte Carlo method is used to study a simple model of two-dimensional interacting quadrupoles on ionic square lattice with anisotropic strength provided by the ionic lattice. Order parameter, susceptibility and correlation function data, show that this system form an ordered structure with p(2×1) symmetry at low temperature. The p(2×1) structure undergoes an order-disorder phase transition into disordered (1×1) phase at 8.3K. The two-point correlation function show exponential dependence on distance both above and below the transition temperature. At Tc the two-point correlation function shows a power law dependence on distance, e.g. C(r) ~ 1η. The value of the exponent η at Tc shows small deviation from the Ising value and indicates that this system falls into the same universality class as the XY model with cubic anisotropy. This model can be applied to prototypical quadrupoles physisorbed systems as N2 on NaCl(100).

Application of the correlation constrained multivariate curve resolution alternating least-squares method for analyte quantitation in the presence of unexpected interferences using first-order instrumental data.

PubMed

Goicoechea, Héctor C; Olivieri, Alejandro C; Tauler, Romà

2010-03-01

Correlation constrained multivariate curve resolution-alternating least-squares is shown to be a feasible method for processing first-order instrumental data and achieve analyte quantitation in the presence of unexpected interferences. Both for simulated and experimental data sets, the proposed method could correctly retrieve the analyte and interference spectral profiles and perform accurate estimations of analyte concentrations in test samples. Since no information concerning the interferences was present in calibration samples, the proposed multivariate calibration approach including the correlation constraint facilitates the achievement of the so-called second-order advantage for the analyte of interest, which is known to be present for more complex higher-order richer instrumental data. The proposed method is tested using a simulated data set and two experimental data systems, one for the determination of ascorbic acid in powder juices using UV-visible absorption spectral data, and another for the determination of tetracycline in serum samples using fluorescence emission spectroscopy.

Scalable, efficient ASICS for the square kilometre array: From A/D conversion to central correlation

NASA Astrophysics Data System (ADS)

Schmatz, M. L.; Jongerius, R.; Dittmann, G.; Anghel, A.; Engbersen, T.; van Lunteren, J.; Buchmann, P.

2014-05-01

The Square Kilometre Array (SKA) is a future radio telescope, currently being designed by the worldwide radio-astronomy community. During the first of two construction phases, more than 250,000 antennas will be deployed, clustered in aperture-array stations. The antennas will generate 2.5 Pb/s of data, which needs to be processed in real time. For the processing stages from A/D conversion to central correlation, we propose an ASIC solution using only three chip architectures. The architecture is scalable - additional chips support additional antennas or beams - and versatile - it can relocate its receiver band within a range of a few MHz up to 4GHz. This flexibility makes it applicable to both SKA phases 1 and 2. The proposed chips implement an antenna and station processor for 289 antennas with a power consumption on the order of 600W and a correlator, including corner turn, for 911 stations on the order of 90 kW.

Pearson's chi-square test and rank correlation inferences for clustered data.

PubMed

Shih, Joanna H; Fay, Michael P

2017-09-01

Pearson's chi-square test has been widely used in testing for association between two categorical responses. Spearman rank correlation and Kendall's tau are often used for measuring and testing association between two continuous or ordered categorical responses. However, the established statistical properties of these tests are only valid when each pair of responses are independent, where each sampling unit has only one pair of responses. When each sampling unit consists of a cluster of paired responses, the assumption of independent pairs is violated. In this article, we apply the within-cluster resampling technique to U-statistics to form new tests and rank-based correlation estimators for possibly tied clustered data. We develop large sample properties of the new proposed tests and estimators and evaluate their performance by simulations. The proposed methods are applied to a data set collected from a PET/CT imaging study for illustration. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Erratum: Measurement of the electron charge asymmetry in $$\\boldsymbol{p\\bar{p}\\rightarrow W+X \\rightarrow e\

DOE PAGES

Abazov, Victor Mukhamedovich

2015-04-30

The recent paper on the charge asymmetry for electrons from W boson decay has an error in the Tables VII to XI that show the correlation coefficients of systematic uncertainties. Furthermore, the correlation matrix elements shown in the original publication were the square roots of the calculated values.

A Note on the Reliability Coefficients for Item Response Model-Based Ability Estimates

ERIC Educational Resources Information Center

Kim, Seonghoon

2012-01-01

Assuming item parameters on a test are known constants, the reliability coefficient for item response theory (IRT) ability estimates is defined for a population of examinees in two different ways: as (a) the product-moment correlation between ability estimates on two parallel forms of a test and (b) the squared correlation between the true…

Examining the Reliability of Interval Level Data Using Root Mean Square Differences and Concordance Correlation Coefficients

ERIC Educational Resources Information Center

Barchard, Kimberly A.

2012-01-01

This article introduces new statistics for evaluating score consistency. Psychologists usually use correlations to measure the degree of linear relationship between 2 sets of scores, ignoring differences in means and standard deviations. In medicine, biology, chemistry, and physics, a more stringent criterion is often used: the extent to which…

Sensing Strategies for Disambiguating among Multiple Objects in Known Poses.

DTIC Science & Technology

1985-08-01

ELEMENT. PROIECT. TASK Artificial Inteligence Laboratory AE OKUI UBR 545 Technology Square Cambridge, MA 021.39 11. CONTROLLING OFFICE NAME AND ADDRESS 12...AD-Ali65 912 SENSING STRATEGIES FOR DISAMBIGURTING MONG MULTIPLE 1/1 OBJECTS IN KNOWN POSES(U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL ...or Dist Special 1 ’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 855 August, 1985 Sensing Strategies for

Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.

PubMed

Ho, Kevin I-J; Leung, Chi-Sing; Sum, John

2010-06-01

In the last two decades, many online fault/noise injection algorithms have been developed to attain a fault tolerant neural network. However, not much theoretical works related to their convergence and objective functions have been reported. This paper studies six common fault/noise-injection-based online learning algorithms for radial basis function (RBF) networks, namely 1) injecting additive input noise, 2) injecting additive/multiplicative weight noise, 3) injecting multiplicative node noise, 4) injecting multiweight fault (random disconnection of weights), 5) injecting multinode fault during training, and 6) weight decay with injecting multinode fault. Based on the Gladyshev theorem, we show that the convergence of these six online algorithms is almost sure. Moreover, their true objective functions being minimized are derived. For injecting additive input noise during training, the objective function is identical to that of the Tikhonov regularizer approach. For injecting additive/multiplicative weight noise during training, the objective function is the simple mean square training error. Thus, injecting additive/multiplicative weight noise during training cannot improve the fault tolerance of an RBF network. Similar to injective additive input noise, the objective functions of other fault/noise-injection-based online algorithms contain a mean square error term and a specialized regularization term.

Simulation and Testing of a Linear Array of Modified Four-Square Feed Antennas for the Tianlai Cylindrical Radio Telescope

NASA Astrophysics Data System (ADS)

Cianciara, Aleksander J.; Anderson, Christopher J.; Chen, Xuelei; Chen, Zhiping; Geng, Jingchao; Li, Jixia; Liu, Chao; Liu, Tao; Lu, Wing; Peterson, Jeffrey B.; Shi, Huli; Steffel, Catherine N.; Stebbins, Albert; Stucky, Thomas; Sun, Shijie; Timbie, Peter T.; Wang, Yougang; Wu, Fengquan; Zhang, Juyong

A wide bandwidth, dual polarized, modified four-square antenna is presented as a feed antenna for radio astronomical measurements. A linear array of these antennas is used as a line-feed for cylindrical reflectors for Tianlai, a radio interferometer designed for 21cm intensity mapping. Simulations of the feed antenna beam patterns and scattering parameters are compared to experimental results at multiple frequencies across the 650-1420MHz range. Simulations of the beam patterns of the combined feed array/reflector are presented as well.

Introductory Statistics in the Garden

ERIC Educational Resources Information Center

Wagaman, John C.

2017-01-01

This article describes four semesters of introductory statistics courses that incorporate service learning and gardening into the curriculum with applications of the binomial distribution, least squares regression and hypothesis testing. The activities span multiple semesters and are iterative in nature.

GSTAR-SUR Modeling With Calendar Variations And Intervention To Forecast Outflow Of Currencies In Java Indonesia

NASA Astrophysics Data System (ADS)

Akbar, M. S.; Setiawan; Suhartono; Ruchjana, B. N.; Riyadi, M. A. A.

2018-03-01

Ordinary Least Squares (OLS) is general method to estimates Generalized Space Time Autoregressive (GSTAR) parameters. But in some cases, the residuals of GSTAR are correlated between location. If OLS is applied to this case, then the estimators are inefficient. Generalized Least Squares (GLS) is a method used in Seemingly Unrelated Regression (SUR) model. This method estimated parameters of some models with residuals between equations are correlated. Simulation study shows that GSTAR with GLS method for estimating parameters (GSTAR-SUR) is more efficient than GSTAR-OLS method. The purpose of this research is to apply GSTAR-SUR with calendar variation and intervention as exogenous variable (GSTARX-SUR) for forecast outflow of currency in Java, Indonesia. As a result, GSTARX-SUR provides better performance than GSTARX-OLS.

Collective charge excitations and the metal-insulator transition in the square lattice Hubbard-Coulomb model

DOE PAGES

Ulybyshev, Maksim; Winterowd, Christopher; Zafeiropoulos, Savvas

2017-11-09

Here in this article, we discuss the nontrivial collective charge excitations (plasmons) of the extended square lattice Hubbard model. Using a fully nonperturbative approach, we employ the hybrid Monte Carlo algorithm to simulate the system at half-filling. A modified Backus-Gilbert method is introduced to obtain the spectral functions via numerical analytic continuation. We directly compute the single-particle density of states which demonstrates the formation of Hubbard bands in the strongly correlated phase. The momentum-resolved charge susceptibility also is computed on the basis of the Euclidean charge-density-density correlator. In agreement with previous extended dynamical mean-field theory studies, we find that, atmore » high strength of the electron-electron interaction, the plasmon dispersion develops two branches.« less

Collective charge excitations and the metal-insulator transition in the square lattice Hubbard-Coulomb model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ulybyshev, Maksim; Winterowd, Christopher; Zafeiropoulos, Savvas

Here in this article, we discuss the nontrivial collective charge excitations (plasmons) of the extended square lattice Hubbard model. Using a fully nonperturbative approach, we employ the hybrid Monte Carlo algorithm to simulate the system at half-filling. A modified Backus-Gilbert method is introduced to obtain the spectral functions via numerical analytic continuation. We directly compute the single-particle density of states which demonstrates the formation of Hubbard bands in the strongly correlated phase. The momentum-resolved charge susceptibility also is computed on the basis of the Euclidean charge-density-density correlator. In agreement with previous extended dynamical mean-field theory studies, we find that, atmore » high strength of the electron-electron interaction, the plasmon dispersion develops two branches.« less

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K

2018-01-03

Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.

Direction information in multiple object tracking is limited by a graded resource.

PubMed

Horowitz, Todd S; Cohen, Michael A

2010-10-01

Is multiple object tracking (MOT) limited by a fixed set of structures (slots), a limited but divisible resource, or both? Here, we answer this question by measuring the precision of the direction representation for tracked targets. The signature of a limited resource is a decrease in precision as the square root of the tracking load. The signature of fixed slots is a fixed precision. Hybrid models predict a rapid decrease to asymptotic precision. In two experiments, observers tracked moving disks and reported target motion direction by adjusting a probe arrow. We derived the precision of representation of correctly tracked targets using a mixture distribution analysis. Precision declined with target load according to the square-root law up to six targets. This finding is inconsistent with both pure and hybrid slot models. Instead, directional information in MOT appears to be limited by a continuously divisible resource.

Four-Dimensional Golden Search

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fenimore, Edward E.

2015-02-25

The Golden search technique is a method to search a multiple-dimension space to find the minimum. It basically subdivides the possible ranges of parameters until it brackets, to within an arbitrarily small distance, the minimum. It has the advantages that (1) the function to be minimized can be non-linear, (2) it does not require derivatives of the function, (3) the convergence criterion does not depend on the magnitude of the function. Thus, if the function is a goodness of fit parameter such as chi-square, the convergence does not depend on the noise being correctly estimated or the function correctly followingmore » the chi-square statistic. And, (4) the convergence criterion does not depend on the shape of the function. Thus, long shallow surfaces can be searched without the problem of premature convergence. As with many methods, the Golden search technique can be confused by surfaces with multiple minima.« less

Liquid fuel spray processes in high-pressure gas flow

NASA Technical Reports Server (NTRS)

Ingebo, R. D.

1985-01-01

Atomization of single liquid jets injected downstream in high pressure and high velocity airflow was investigated to determine the effect of airstream pressure on mean drop size as measured with a scanning radiometer. For aerodynamic - wave breakup of liquid jets, the ratio of orifice diameter D sub o to measured mean drop diameter D sub m which is assumed equal to D sub 32 or Sauter mean diameter, was correlated with the product of the Weber and Reynolds numbers WeRe and the dimensionless group G1/square root of c, where G is the gravitational acceleration, 1 the mean free molecular path, and square root of C the root mean square velocity, as follows; D sub o/D sub 32 = 1.2 (WeRe) to the 0.4 (G1/square root of c) to the 0.15 for values of WeRe 1 million and an airstream pressure range of 0.10 to 2.10 MPa.

Liquid fuel spray processes in high-pressure gas flow

NASA Technical Reports Server (NTRS)

Ingebo, R. D.

1986-01-01

Atomization of single liquid jets injected downstream in high pressure and high velocity airflow was investigated to determine the effect of airstream pressure on mean drop size as measured with a scanning radiometer. For aerodynamic - wave breakup of liquid jets, the ratio of orifice diameter D sub o to measured mean drop diameter D sub m which is assumed equal to D sub 32 or Sauter mean diameter, was correlated with the product of the Weber and Reynolds numbers WeRe and the dimensionless group G1/square root of c, where G is the gravitational acceleration, 1 the mean free molecular path, and square root of C the root mean square velocity, as follows; D sub o/D sub 32 = 1.2 (WeRe) to the 0.4 (G1/square root of c) to the 0.15 for values of WeRe 1 million and an airstream pressure range of 0.10 to 2.10 MPa.

An Evaluation of Population Density Mapping and Built up Area Estimates in Sri Lanka Using Multiple Methodologies

NASA Astrophysics Data System (ADS)

Engstrom, R.; Soundararajan, V.; Newhouse, D.

2017-12-01

In this study we examine how well multiple population density and built up estimates that utilize satellite data compare in Sri Lanka. The population relationship is examined at the Gram Niladhari (GN) level, the lowest administrative unit in Sri Lanka from the 2011 census. For this study we have two spatial domains, the whole country and a 3,500km2 sub-sample, for which we have complete high spatial resolution imagery coverage. For both the entire country and the sub-sample we examine how consistent are the existing publicly available measures of population constructed from satellite imagery at predicting population density? For just the sub-sample we examine how well do a suite of values derived from high spatial resolution satellite imagery predict population density and how does our built up area estimate compare to other publicly available estimates. Population measures were obtained from the Sri Lankan census, and were downloaded from Facebook, WorldPoP, GPW, and Landscan. Percentage built-up area at the GN level was calculated from three sources: Facebook, Global Urban Footprint (GUF), and the Global Human Settlement Layer (GHSL). For the sub-sample we have derived a variety of indicators from the high spatial resolution imagery. Using deep learning convolutional neural networks, an object oriented, and a non-overlapping block, spatial feature approach. Variables calculated include: cars, shadows (a proxy for building height), built up area, and buildings, roof types, roads, type of agriculture, NDVI, Pantex, and Histogram of Oriented Gradients (HOG) and others. Results indicate that population estimates are accurate at the higher, DS Division level but not necessarily at the GN level. Estimates from Facebook correlated well with census population (GN correlation of 0.91) but measures from GPW and WorldPop are more weakly correlated (0.64 and 0.34). Estimates of built-up area appear to be reliable. In the 32 DSD-subsample, Facebook's built- up area measure is highly correlated with our built-up measure (correlation of 0.9). Preliminary regression results based on variables selected from Lasso-regressions indicate that satellite indicators have exceptionally strong predictive power in predicting GN level population level and density with an out of sample r-squared of 0.75 and 0.72 respectively.

Ethnic disparities in the risk of colorectal adenomas associated with lipid levels: a retrospective multiethnic study.

PubMed

Davis-Yadley, Ashley H; Lipka, Seth; Shen, Huafeng; Devanney, Valerie; Swarup, Supreeya; Barnowsky, Alex; Silpe, Jeff; Mosdale, Josh; Pan, Qinshi; Fridlyand, Svetlana; Sreeharshan, Suhas; Abraham, Albin; Viswanathan, Prakash; Krishnamachari, Bhuma

2015-03-01

Although data exists showing that uncontrolled lipid levels in white and black patients is associated with colorectal adenomas, there are currently no studies looking only at the Hispanic population. With the rapid increase in the Hispanic population, we aimed to look at their risk of colorectal adenomas in association with lipid levels. We retrospectively analyzed 1473 patients undergoing colonoscopy from 2009 to 2011 at a community hospital. Statistical analysis was performed using Chi-squared for categorical variables and t test for continuous variables with age-, gender-, and race-adjusted odds ratios. Unconditional logistic regression model was used to estimate 95 % confidence intervals (CI). SAS 9.3 software was used to perform all statistical analysis. In our general population, there was an association with elevated triglyceride levels greater than 150 and presence of multiple colorectal adenomas with odds ratio (OR) 1.60 (1.03, 2.48). There was an association with proximal colon adenomas and cholesterol levels between 200 and 239 with OR 1.57 (1.07, 2.30), and low-density lipoprotein (LDL) levels of greater than 130 with OR 1.54 (1.04, 2.30). There was no association between high-density lipoproteins (HDL) levels and colorectal adenomas. The Hispanic population showed no statistical correlation between elevated triglycerides, cholesterol, or LDL with the presence, size, location, or multiplicity of colorectal adenomas. We found a significant correlation between elevated lipid levels and colorectal adenomas in white and black patients; however, there was no such association in the Hispanic population. This finding can possibly be due to environmental factors such as dietary, colonic flora, or genetic susceptibility, which fosters further investigation and research.

Quality of life profile and correlated factors in chronic leg ulcer patients in the mid-west of São Paulo State, Brazil*

PubMed Central

Wachholz, Patrick Alexander; Masuda, Paula Yoshiko; Nascimento, Dejair Caitano; Taira, Cecilia Midori Higashi; Cleto, Norma Gondim

2014-01-01

BACKGROUND Chronic leg ulcer may have an impact on patients' quality of life. OBJECTIVES This study aimed to identify the impact of leg ulcers on patient's quality of life using the Dermatology Life Quality Index and to define the main factors correlated with this perception. METHOD Cross-sectional, non-probabilistic sampling study. We included patients with chronic leg ulcers being treated for at least 3 months. A sociodemographic and clinical survey was conducted to assess the profile of the ulcers. We administered a screening for depressive symptoms and the Dermatology Life Quality Index. We performed a descriptive statistical analysis, chi-square test and Mann-Whitney test for categorical data, Pearson for numeric variables, and multiple regression for categorical data. RESULTS Forty-one patients were assessed. Their mean age was 61.78 years. Venous ulcers (48.8%) were the most prevalent. Seventy-three percent of the sample perceived no impact/low impact on quality of life in the past week, and 26.8% perceived moderate/high impact. A multiple regression analysis identified the causes of lesion, pain related to the ulcers, time of onset, and severity of the depressive symptoms as the variables that had an influence on quality of life. CONCLUSIONS The majority of the sample perceived low or no impact of the condition on the quality of the life. The variables etiology of the lesion (p<0.001), pain related to the ulcers (p=0.001), time of onset (p=0.006), and severity of the depressive symptoms (p<0.001) had an influence on the quality of life, suggesting the need for further studies with more robust designs to confirm the causal relationship between these characteristics and quality of life. PMID:24626651

A clinical test of stepping and change of direction to identify multiple falling older adults.

PubMed

Dite, Wayne; Temple, Viviene A

2002-11-01

To establish the reliability and validity of a new clinical test of dynamic standing balance, the Four Square Step Test (FSST), to evaluate its sensitivity, specificity, and predictive value in identifying subjects who fall, and to compare it with 3 established balance and mobility tests. A 3-group comparison performed by using 3 validated tests and 1 new test. A rehabilitation center and university medical school in Australia. Eighty-one community-dwelling adults over the age of 65 years. Subjects were age- and gender-matched to form 3 groups: multiple fallers, nonmultiple fallers, and healthy comparisons. Not applicable. Time to complete the FSST and Timed Up and Go test and the number of steps to complete the Step Test and Functional Reach Test distance. High reliability was found for interrater (n=30, intraclass correlation coefficient [ICC]=.99) and retest reliability (n=20, ICC=.98). Evidence for validity was found through correlation with other existing balance tests. Validity was supported, with the FSST showing significantly better performance scores (P<.01) for each of the healthier and less impaired groups. The FSST also revealed a sensitivity of 85%, a specificity of 88% to 100%, and a positive predictive value of 86%. As a clinical test, the FSST is reliable, valid, easy to score, quick to administer, requires little space, and needs no special equipment. It is unique in that it involves stepping over low objects (2.5cm) and movement in 4 directions. The FSST had higher combined sensitivity and specificity for identifying differences between groups in the selected sample population of older adults than the 3 tests with which it was compared. Copyright 2002 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

Association between non-cholesterol sterol concentrations and Achilles tendon thickness in patients with genetic familial hypercholesterolemia.

PubMed

Baila-Rueda, Lucía; Lamiquiz-Moneo, Itziar; Jarauta, Estíbaliz; Mateo-Gallego, Rocío; Perez-Calahorra, Sofía; Marco-Benedí, Victoria; Bea, Ana M; Cenarro, Ana; Civeira, Fernando

2018-01-15

Familial hypercholesterolemia (FH) is a genetic disorder that result in abnormally high low-density lipoprotein cholesterol levels, markedly increased risk of coronary heart disease (CHD) and tendon xanthomas (TX). However, the clinical expression is highly variable. TX are present in other metabolic diseases that associate increased sterol concentration. If non-cholesterol sterols are involved in the development of TX in FH has not been analyzed. Clinical and biochemical characteristics, non-cholesterol sterols concentrations and Aquilles tendon thickness were determined in subjects with genetic FH with (n = 63) and without (n = 40) TX. Student-t test o Mann-Whitney test were used accordingly. Categorical variables were compared using a Chi square test. ANOVA and Kruskal-Wallis tests were performed to multiple independent variables comparison. Post hoc adjusted comparisons were performed with Bonferroni correction when applicable. Correlations of parameters in selected groups were calculated applying the non-parametric Spearman correlation procedure. To identify variables associated with Achilles tendon thickness changes, multiple linear regression were applied. Patients with TX presented higher concentrations of non-cholesterol sterols in plasma than patients without xanthomas (P = 0.006 and 0.034, respectively). Furthermore, there was a significant association between 5α-cholestanol, β-sitosterol, desmosterol, 24S-hydroxycholesterol and 27-hydroxycholesterol concentrations and Achilles tendon thickness (p = 0.002, 0.012, 0.020, 0.045 and 0.040, respectively). Our results indicate that non-cholesterol sterol concentrations are associated with the presence of TX. Since cholesterol and non-cholesterol sterols are present in the same lipoproteins, further studies would be needed to elucidate their potential role in the development of TX.

A survey and evaluations of histogram-based statistics in alignment-free sequence comparison.

PubMed

Luczak, Brian B; James, Benjamin T; Girgis, Hani Z

2017-12-06

Since the dawn of the bioinformatics field, sequence alignment scores have been the main method for comparing sequences. However, alignment algorithms are quadratic, requiring long execution time. As alternatives, scientists have developed tens of alignment-free statistics for measuring the similarity between two sequences. We surveyed tens of alignment-free k-mer statistics. Additionally, we evaluated 33 statistics and multiplicative combinations between the statistics and/or their squares. These statistics are calculated on two k-mer histograms representing two sequences. Our evaluations using global alignment scores revealed that the majority of the statistics are sensitive and capable of finding similar sequences to a query sequence. Therefore, any of these statistics can filter out dissimilar sequences quickly. Further, we observed that multiplicative combinations of the statistics are highly correlated with the identity score. Furthermore, combinations involving sequence length difference or Earth Mover's distance, which takes the length difference into account, are always among the highest correlated paired statistics with identity scores. Similarly, paired statistics including length difference or Earth Mover's distance are among the best performers in finding the K-closest sequences. Interestingly, similar performance can be obtained using histograms of shorter words, resulting in reducing the memory requirement and increasing the speed remarkably. Moreover, we found that simple single statistics are sufficient for processing next-generation sequencing reads and for applications relying on local alignment. Finally, we measured the time requirement of each statistic. The survey and the evaluations will help scientists with identifying efficient alternatives to the costly alignment algorithm, saving thousands of computational hours. The source code of the benchmarking tool is available as Supplementary Materials. © The Author 2017. Published by Oxford University Press.

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Reversible ratchet effects for vortices in conformal pinning arrays

DOE PAGES

Reichhardt, Charles; Ray, Dipanjan; Reichhardt, Cynthia Jane Olson

2015-05-04

A conformal transformation of a uniform triangular pinning array produces a structure called a conformal crystal which preserves the sixfold ordering of the original lattice but contains a gradient in the pinning density. Here we use numerical simulations to show that vortices in type-II superconductors driven with an ac drive over gradient pinning arrays produce the most pronounced ratchet effect over a wide range of parameters for a conformal array, while square gradient or random gradient arrays with equivalent pinning densities give reduced ratchet effects. In the conformal array, the larger spacing of the pinning sites in the direction transversemore » to the ac drive permits easy funneling of interstitial vortices for one driving direction, producing the enhanced ratchet effect. In the square array, the transverse spacing between pinning sites is uniform, giving no asymmetry in the funneling of the vortices as the driving direction switches, while in the random array, there are numerous easy-flow channels present for either direction of drive. We find multiple ratchet reversals in the conformal arrays as a function of vortex density and ac amplitude, and correlate the features with a reversal in the vortex ordering, which is greater for motion in the ratchet direction. In conclusion, the enhanced conformal pinning ratchet effect can also be realized for colloidal particles moving over a conformal array, indicating the general usefulness of conformal structures for controlling the motion of particles.« less

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Application of Molecular Dynamics Simulations in Molecular Property Prediction II: Diffusion Coefficient

PubMed Central

Wang, Junmei; Hou, Tingjun

2011-01-01

In this work, we have evaluated how well the General AMBER force field (GAFF) performs in studying the dynamic properties of liquids. Diffusion coefficients (D) have been predicted for 17 solvents, 5 organic compounds in aqueous solutions, 4 proteins in aqueous solutions, and 9 organic compounds in non-aqueous solutions. An efficient sampling strategy has been proposed and tested in the calculation of the diffusion coefficients of solutes in solutions. There are two major findings of this study. First of all, the diffusion coefficients of organic solutes in aqueous solution can be well predicted: the average unsigned error (AUE) and the root-mean-square error (RMSE) are 0.137 and 0.171 ×10−5 cm−2s−1, respectively. Second, although the absolute values of D cannot be predicted, good correlations have been achieved for 8 organic solvents with experimental data (R2 = 0.784), 4 proteins in aqueous solutions (R2 = 0.996) and 9 organic compounds in non-aqueous solutions (R2 = 0.834). The temperature dependent behaviors of three solvents, namely, TIP3P water, dimethyl sulfoxide (DMSO) and cyclohexane have been studied. The major MD settings, such as the sizes of simulation boxes and with/without wrapping the coordinates of MD snapshots into the primary simulation boxes have been explored. We have concluded that our sampling strategy that averaging the mean square displacement (MSD) collected in multiple short-MD simulations is efficient in predicting diffusion coefficients of solutes at infinite dilution. PMID:21953689

Incidence and factors associated with flare-ups in a post graduate programme in the indian population.

PubMed

Pamboo, Jaya; Hans, Manoj-Kumar; Kumaraswamy, Bangalore-Niranjan; Chander, Subhash; Bhaskaran, Sajeev

2014-12-01

The study had twin objectives: to assess the incidence of flare-ups (a severe problem requiring an unscheduled visit and treatment) among patients who received endodontic treatment in the Department of Conservative Dentistry and Endodontics in Vyas Dental college and hospital, Jodhpur during a period of one year, and also to examine the correlation with pre-operative and operative variables. Data was collected from 1023 teeth from 916 patients who had received endodontic treatment over a 12- month period. Information was obtained for each patient treated, including pulp and peri-radicular diagnosis for the tooth, presence of pre-operatory pain, type of medication being used, type of instrumentation technique used and number of appointments needed to complete the root canal treatment. The results showed an incidence of 2.35% for flare-ups from 1023 endodontically treated teeth. Statistical analysis was done using the chi-square test. Flare-ups were found to be affected significantly by gender of patient, presence of radiolucent lesions, patients taking pre-operative analgesic or anti-inflammatory drugs and on type of instrumentation technique. In contrast, there was no correlation between flare-ups and age, different arch/tooth groups and single or multiple visit endodontics. Key words:Anti-inflammatory, flare-ups, instrumentation, prospective.

Incidence and factors associated with flare-ups in a post graduate programme in the indian population

PubMed Central

Pamboo, Jaya; Kumaraswamy, Bangalore-Niranjan; Chander, Subhash; Bhaskaran, Sajeev

2014-01-01

Objectives: The study had twin objectives: to assess the incidence of flare-ups (a severe problem requiring an unscheduled visit and treatment) among patients who received endodontic treatment in the Department of Conservative Dentistry and Endodontics in Vyas Dental college and hospital, Jodhpur during a period of one year, and also to examine the correlation with pre-operative and operative variables. Material and Methods: Data was collected from 1023 teeth from 916 patients who had received endodontic treatment over a 12- month period. Information was obtained for each patient treated, including pulp and peri-radicular diagnosis for the tooth, presence of pre-operatory pain, type of medication being used, type of instrumentation technique used and number of appointments needed to complete the root canal treatment. Results: The results showed an incidence of 2.35% for flare-ups from 1023 endodontically treated teeth. Statistical analysis was done using the chi-square test. Conclusions: Flare-ups were found to be affected significantly by gender of patient, presence of radiolucent lesions, patients taking pre-operative analgesic or anti-inflammatory drugs and on type of instrumentation technique. In contrast, there was no correlation between flare-ups and age, different arch/tooth groups and single or multiple visit endodontics. Key words:Anti-inflammatory, flare-ups, instrumentation, prospective. PMID:25674318

PREVALENCE OF ANTIBODIES AGAINST INFLUENZA VIRUS IN NON-VACCINATED EQUINES FROM THE BRAZILIAN PANTANAL

PubMed Central

Silva, Lucas Gaíva E; Borges, Alice Mamede Costa Marques; Villalobos, Eliana Monteforte Cassaro; Lara, Maria do Carmo Custodio Souza Hunold; Cunha, Elenice Maria Siquetin; de Oliveira, Anderson Castro Soares; Braga, Ísis Assis; Aguiar, Daniel Moura

2014-01-01

The prevalence of antibodies against Equine Influenza Virus (EIV) was determined in 529 equines living on ranches in the municipality of Poconé, Pantanal area of Brazil, by means of the hemagglutination inhibition test, using subtype H3N8 as antigen. The distribution and possible association among positive animal and ranches were evaluated by the chi-square test, spatial autoregressive and multiple linear regression models. The prevalence of antibodies against EIV was estimated at 45.2% (95% CI 30.2 - 61.1%) with titers ranging from 20 to 1,280 HAU. Seropositive equines were found on 92.0% of the surveyed ranches. Equine from non-flooded ranches (66.5%) and negativity in equine infectious anemia virus (EIAV) (61.7%) were associated with antibodies against EIV. No spatial correlation was found among the ranches, but the ones located in non-flooded areas were associated with antibodies against EIV. A negative correlation was found between the prevalence of antibodies against EIV and the presence of EIAV positive animals on the ranches. The high prevalence of antibodies against EIV detected in this study suggests that the virus is circulating among the animals, and this statistical analysis indicates that the movement and aggregation of animals are factors associated to the transmission of the virus in the region. PMID:25351542

Application of tristimulus colorimetry to estimate the carotenoids content in ultrafrozen orange juices.

PubMed

Meléndez-Martínez, Antonio J; Vicario, Isabel M; Heredia, Francisco J

2003-12-03

Tristimulus Colorimetry was applied to characterize the color of Valencia late orange juices. Color measurements were made against white background and black background. The profile of the main carotenoids related to the color of the juices was determined by HPLC. Significant correlations (p < 0.05) between b*, Cab* and h(ab) and the content of beta-cryptoxanthin, lutein + zeaxanthin and beta-carotene were found. The correlations between the color parameters L*, a*, b*, Cab* and h(ab) and the carotenoids content were also explored by partial least squares. The results obtained have shown that it is possible to obtain equations, by means of multiple regression models, which allow the determination of the individual carotenoid levels from the CIELAB color parameters, with R2 values always over 0.9. In this sense, equations have been proposed to calculate the retinol equivalents (1 RE = 1 microgram retinol = 12 micrograms beta-carotene = 24 micrograms alpha-carotene = 24 micrograms beta-cryptoxanthin) of the orange juice analyzed as a function of the color parameters calculated from measurement made against white and black backgrounds. The average RE per liter of juice obtained by HPLC was 51.07 +/- 18.89, whereas employing these equations, average RE values obtained were 51.16 +/- 1.36 and 51.21 +/- 1.70 for white background and black background, respectively.

Dynamics in entangled polyethylene melts using coarse-grained models

NASA Astrophysics Data System (ADS)

Peters, Brandon L.; Grest, Gary S.; Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora

Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion on multiple length scales. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using polyethylene (PE) as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion (iBi) with 2-6 methyl groups per CG bead from all fully atomistic melt simulations for short chains. While the iBi methods produces non-bonded potentials which give excellent agreement for the atomistic and CG pair correlation functions, the pressure P = 100-500MPa for the CG model. Correcting for potential so P 0 leads to non-bonded models with slightly smaller effective diameter and much deeper minimum. However, both the pressure and non-pressure corrected CG models give similar results for mean squared displacement (MSD) and the stress auto correlation function G(t) for PE melts above the melting point. The time rescaling factor between CG and atomistic models is found to be nearly the same for both CG models. Transferability of potential for different temperatures was tested by comparing the MSD and G(t) for potentials generated at different temperatures.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Multifactor analysis and simulation of the surface runoff and soil infiltration at different slope gradients

NASA Astrophysics Data System (ADS)

Huang, J.; Kang, Q.; Yang, J. X.; Jin, P. W.

2017-08-01

The surface runoff and soil infiltration exert significant influence on soil erosion. The effects of slope gradient/length (SG/SL), individual rainfall amount/intensity (IRA/IRI), vegetation cover (VC) and antecedent soil moisture (ASM) on the runoff depth (RD) and soil infiltration (INF) were evaluated in a series of natural rainfall experiments in the South of China. RD is found to correlate positively with IRA, IRI, and ASM factors and negatively with SG and VC. RD decreased followed by its increase with SG and ASM, it increased with a further decrease with SL, exhibited a linear growth with IRA and IRI, and exponential drop with VC. Meanwhile, INF exhibits a positive correlation with SL, IRA and IRI and VC, and a negative one with SG and ASM. INF was going up and then down with SG, linearly rising with SL, IRA and IRI, increasing by a logit function with VC, and linearly falling with ASM. The VC level above 60% can effectively lower the surface runoff and significantly enhance soil infiltration. Two RD and INF prediction models, accounting for the above six factors, were constructed using the multiple nonlinear regression method. The verification of those models disclosed a high Nash-Sutcliffe coefficient and low root-mean-square error, demonstrating good predictability of both models.

Life satisfaction in adult survivors of childhood brain tumors.

PubMed

Crom, Deborah B; Li, Zhenghong; Brinkman, Tara M; Hudson, Melissa M; Armstrong, Gregory T; Neglia, Joseph; Ness, Kirsten K

2014-01-01

Adult survivors of childhood brain tumors experience multiple, significant, lifelong deficits as a consequence of their malignancy and therapy. Current survivorship literature documents the substantial impact such impairments have on survivors' physical health and quality of life. Psychosocial reports detail educational, cognitive, and emotional limitations characterizing survivors as especially fragile, often incompetent, and unreliable in evaluating their circumstances. Anecdotal data suggest some survivors report life experiences similar to those of healthy controls. The aim of our investigation was to determine whether life satisfaction in adult survivors of childhood brain tumors differs from that of healthy controls and to identify potential predictors of life satisfaction in survivors. This cross-sectional study compared 78 brain tumor survivors with population-based matched controls. Chi-square tests, t tests, and linear regression models were used to investigate patterns of life satisfaction and identify potential correlates. Results indicated that life satisfaction of adult survivors of childhood brain tumors was similar to that of healthy controls. Survivors' general health expectations emerged as the primary correlate of life satisfaction. Understanding life satisfaction as an important variable will optimize the design of strategies to enhance participation in follow-up care, reduce suffering, and optimize quality of life in this vulnerable population. © 2014 by Association of Pediatric Hematology/Oncology Nurses.

Rapid non-destructive assessment of pork edible quality by using VIS/NIR spectroscopic technique

NASA Astrophysics Data System (ADS)

Zhang, Leilei; Peng, Yankun; Dhakal, Sagar; Song, Yulin; Zhao, Juan; Zhao, Songwei

2013-05-01

The objectives of this research were to develop a rapid non-destructive method to evaluate the edible quality of chilled pork. A total of 42 samples were packed in seal plastic bags and stored at 4°C for 1 to 21 days. Reflectance spectra were collected from visible/near-infrared spectroscopy system in the range of 400nm to 1100nm. Microbiological, physicochemical and organoleptic characteristics such as the total viable counts (TVC), total volatile basic-nitrogen (TVB-N), pH value and color parameters L* were determined to appraise pork edible quality. Savitzky-Golay (SG) based on five and eleven smoothing points, Multiple Scattering Correlation (MSC) and first derivative pre-processing methods were employed to eliminate the spectra noise. The support vector machines (SVM) and partial least square regression (PLSR) were applied to establish prediction models using the de-noised spectra. A linear correlation was developed between the VIS/NIR spectroscopy and parameters such as TVC, TVB-N, pH and color parameter L* indexes, which could gain prediction results with Rv of 0.931, 0.844, 0.805 and 0.852, respectively. The results demonstrated that VIS/NIR spectroscopy technique combined with SVM possesses a powerful assessment capability. It can provide a potential tool for detecting pork edible quality rapidly and non-destructively.

Bayesian Travel Time Inversion adopting Gaussian Process Regression

NASA Astrophysics Data System (ADS)

Mauerberger, S.; Holschneider, M.

2017-12-01

A major application in seismology is the determination of seismic velocity models. Travel time measurements are putting an integral constraint on the velocity between source and receiver. We provide insight into travel time inversion from a correlation-based Bayesian point of view. Therefore, the concept of Gaussian process regression is adopted to estimate a velocity model. The non-linear travel time integral is approximated by a 1st order Taylor expansion. A heuristic covariance describes correlations amongst observations and a priori model. That approach enables us to assess a proxy of the Bayesian posterior distribution at ordinary computational costs. No multi dimensional numeric integration nor excessive sampling is necessary. Instead of stacking the data, we suggest to progressively build the posterior distribution. Incorporating only a single evidence at a time accounts for the deficit of linearization. As a result, the most probable model is given by the posterior mean whereas uncertainties are described by the posterior covariance.As a proof of concept, a synthetic purely 1d model is addressed. Therefore a single source accompanied by multiple receivers is considered on top of a model comprising a discontinuity. We consider travel times of both phases - direct and reflected wave - corrupted by noise. Left and right of the interface are assumed independent where the squared exponential kernel serves as covariance.

Overweight and Physical Inactivity Among African American Students at a Historically Black University.

PubMed

Sa, Jaesin; Heimdal, James; Sbrocco, Tracy; Seo, Dong-Chul; Nelson, Beatrice

2016-02-01

Little is known about correlates of overweight, obesity, and physical inactivity among African American students at historically Black colleges and universities. To assess overweight, obesity, and physical inactivity among African American college students at a historically Black university in Maryland in the USA. Data were collected from 268 African American college students in 2013. Data were analyzed with percentage difference z-tests, chi-square tests, and multiple logistic regression. Cross-sectional survey (student response rate = 49.9%). The overweight/obesity rate of participants was 47.5%, which was higher than that of the U.S. college student population overall (34.1%) and a representative sample of African American college students (38.3%). When age and sex were controlled, a family history of obesity, skipping breakfast, drinking caffeinated drinks, lower family income, and smoking a pipe, cigars, or cigarettes daily were significant correlates of overweight (obesity included). The percentage of physical inactivity was 68.3, and physical inactivity was higher among women and overweight or obese students. Given the high overweight and obesity prevalence among African American college students, historically Black colleges and universities in the USA should increase health promotion efforts targeting weight-related behaviors, particularly physical activity. Copyright © 2016. Published by Elsevier Inc.

Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

NASA Astrophysics Data System (ADS)

Dung Nguyen, The; Kappas, Martin

2017-04-01

In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

Lifestyle factors and dietary intake of Iranian postgraduate students in Universiti Putra Malaysia (UPM)

PubMed Central

Zarei, Maryam; Taib, Mohd Nasir Mohd; Zarei, Fatemeh

2013-01-01

Background: A student’s lifestyle can change notably in a foreign country. The objective of this study was to determine factors associated with the body weight status of Iranian postgraduate students in Universiti Putra Malaysia (UPM) 2009. Methods: A self-administered questionnaire was administered to 210 Iranian postgraduate students at UPM. Anthropometric factors also were measured using standard procedures. Body mass index (BMI) and waist-to-hip ratio (WHR) also were calculated. The chi-squared test, Spearman’s rho, and the Pearson product-moment correlation coefficient were used to determine the associations between the variables that were studied. Multiple linear regression analysis was used to measure the amount of influence a predictor variable had on a outcome variable. Results: There was no significant correlation between nutritional knowledge (P > 0.05), weight-management knowledge (P > 0.05), and smoking (P > 0.05) and BMI. There were statistically significant correlations between gender (P < 0.01), physical activity (P < 0.05), protein (P < 0.01), carbohydrate (P < 0.01), fat (P < 0.01), fiber (P < 0.01), vitamin C (P < 0.05), calcium (P < 0.01), and iron (P < 0.01) and BMI. There were also relationships between body fat (P < 0.01), waist circumference (P < 0.01), hip circumference (P < 0.01) and WHR (P < 0.01) and BMI. Conclusion: Our findings showed the need for a nutrition promotion program for the Iranian students to help them change their negative food habits and improve their lifestyles. PMID:26120404

Postural response latencies are related to balance control during standing and walking in patients with multiple sclerosis

PubMed Central

Huisinga, Jessie M.; St. George, Rebecca J.; Spain, Rebecca; Overs, Shannon; Horak, Fay B.

2015-01-01

Objective To understand examined the relationship between postural response latencies obtained during postural perturbations and representative measures of balance during standing (sway variables) and during walking (trunk motion). Design Cross-sectional Setting University medical center balance disorders laboratory Participants Forty persons with MS were compared with 20 similar aged control subjects. Twenty subjects with MS had normal walking velocity group and 20 had slow walking velocity based on the 25-foot walk time greater than 5 seconds. Interventions None Main Outcome Measures Postural response latency, sway variables, trunk motion variables Results: We found that subjects with MS with either slow or normal walking velocities had significantly longer postural response latencies than the healthy control group. Postural response latency was not correlated with the 25-ft walk time. Postural response latency was significantly correlated with center of pressure sway variables during quiet standing: root mean square (ρ = 0.334, p=0.040), range (ρ=0.385, p=0.017), mean velocity (ρ=0.337, p=0.038), and total sway area (ρ=0.393, p=0.015). Postural response latency was also significantly correlated with motion of the trunk during walking: sagittal plane range of motion (ρ=0.316, p=0.050) and standard deviation of transverse plane range of motion (ρ=-0.430, p=0.006). Conclusions These findings clearly indicate that slow postural responses to external perturbations in patients with MS contribute to disturbances in balance control, both during standing and walking. PMID:24445088

Condom Use at Last Sexual Intercourse and Its Correlates among Males and Females Aged 15–49 Years in Nepal

PubMed Central

Sharma, Bimala; Nam, Eun Woo

2018-01-01

This study aimed to assess the prevalence and correlates of condom use at last sexual intercourse among people aged 15–49 years in Nepal. Secondary data analysis was performed using the Nepal Demographic and Health Survey 2011. The study was restricted to the respondents who reported ever having had sexual intercourse; 9843 females and 3017 males were included. Condom use was assessed by asking if respondents used condoms in their most recent sexual intercourse. Chi-square test and multivariate logistic regression analysis were performed using Complex Sample Analysis Procedure to adjust for sample weight and multistage sampling design. Overall, 7.6% of total, and 16.3% of males and 6.2% of females reported using condoms in their last sexual intercourse. Living in Far-Western region, age and wealth quintile were positively associated with condom use in both males and females. Being unmarried was the most important predictor of condom use among males. Higher education was associated with increased likelihood of condom use in females. However, mobility, having multiple sexual partners, and HIV knowledge were not significant correlates of condom use in both sexes. A big difference was observed in the variance accounted for males and females; indicating use of condoms is poorly predicted by the variables included in the study among females. Condom use was more associated with sociodemographic factors than with sexual behavior and HIV knowledge. PMID:29547564

Three Positive Parenting Practices and Their Correlation with Risk of Childhood Developmental, Social, or Behavioral Delays: An Analysis of the National Survey of Children's Health.

PubMed

Cprek, Sarah E; Williams, Corrine M; Asaolu, Ibitola; Alexander, Linda A; Vanderpool, Robin C

2015-11-01

(1) Investigate the relationship between three specific positive parenting practices (PPP)-reading to children, engaging in storytelling or singing, and eating meals together as a family-and parent-reported risk of developmental, behavioral, or social delays among children between the ages of 1-5 years in the US. (2) Determine if a combination of these parenting practices has an effect on the outcome. Chi square and multiple logistic regression analyses were used to analyze cross-sectional data from the National Survey of Children's Health 2011/2012 in regards to the relationship between each of the three individual PPP as well as a total PPP score and the child's risk of being developmentally, socially, or behaviorally delayed (N = 21,527). Risk of delay was calculated using the Parents' Evaluation of Developmental Status Questionnaire, which is a parental self-report measure that has been correlated with diagnosed child delays. These analyses controlled for poverty and parental education. All analyses were completed using SAS Version 9.3. A strong correlation was found between each of the three PPP as well as the total PPP score and the child's risk of developmental, social, or behavioral delays (p < 0.05 for each test). These associations were found to have a dose-response relationship (p < 0.05 in all but one analysis). Daily engagement in PPP could possibly reduce children's risk of delay, and specifically engaging in all three PPP may have greater benefit.

On the Rapid Computation of Various Polylogarithmic Constants

NASA Technical Reports Server (NTRS)

Bailey, David H.; Borwein, Peter; Plouffe, Simon

1996-01-01

We give algorithms for the computation of the d-th digit of certain transcendental numbers in various bases. These algorithms can be easily implemented (multiple precision arithmetic is not needed), require virtually no memory, and feature run times that scale nearly linearly with the order of the digit desired. They make it feasible to compute, for example, the billionth binary digit of log(2) or pi on a modest workstation in a few hours run time. We demonstrate this technique by computing the ten billionth hexadecimal digit of pi, the billionth hexadecimal digits of pi-squared, log(2) and log-squared(2), and the ten billionth decimal digit of log(9/10). These calculations rest on the observation that very special types of identities exist for certain numbers like pi, pi-squared, log(2) and log-squared(2). These are essentially polylogarithmic ladders in an integer base. A number of these identities that we derive in this work appear to be new, for example a critical identity for pi.

Quality of semen: a 6-year single experience study on 5680 patients.

PubMed

Cozzolino, Mauro; Coccia, Maria E; Picone, Rita

2018-02-08

The aim of our study was to evaluate the quality of semen of a large sample from general healthy population living in Italy, in order to identify possible variables that could influence several parameters of spermiogram. We conducted a cross-sectional study from February 2010 to March 2015, collecting semen samples from the general population. Semen analysis was performed according to the WHO guidelines. The collected data were inserted in a database and processed using the software Stata 12. The Mann - Whitney test was used to assess the relationship of dichotomus variables with the parameters of the spermiogram; Kruskal-Wallis test for variables with more than two categories. We used also Robust regression and Spearman correlation to analyze the relationship between age and the parameters. We collected 5680 samples of semen. The mean age of our patients was 41.4 years old. Mann-Whitney test showed that the citizenship (codified as "Italian/Foreign") influences some parameters: pH, vitality, number of spermatozoa, sperm concentration, with worse results for the Italian group. Kruskal-Wallis test showed that the single nationality influences pH, volume, Sperm motility A-B-C-D, vitality, morphology, number of spermatozoa, sperm concentration. Robust regression showed a relationship between age and several parameters: volume (p=0.04, R squared= 0.0007 β: - 0.06); sperm motility A (p<0.01; R squared 0.0051 β: 0.02); sperm motility B (p<0.01; R squared 0.02 β: -0.35); sperm motility C (p<0.01; R squared 0.01 β: 0.12); sperm motility D (p<0.01; R squared 0.006 β: 0.2); vitality (p<0.01; R squared 0.01 β: -0.32); sperm concentration (p=0.01; R squared 0.001 β: 0.19). Our patients had spermiogram's results quite better than the standard guidelines. Our study showed that the country of origin could be a factor influencing several parameters of the spermiogram in healthy population and through Robust regression confirmed a strict correlation between age and these parameters.

imDEV: a graphical user interface to R multivariate analysis tools in Microsoft Excel

PubMed Central

Grapov, Dmitry; Newman, John W.

2012-01-01

Summary: Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R's multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Availability and implementation: Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010). Contact: John.Newman@ars.usda.gov Supplementary Information: Installation instructions, tutorials and users manual are available at http://sourceforge.net/projects/imdev/. PMID:22815358

ERTS data user investigation to develop a multistage forest sampling inventory system

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A unique digital timber volume estimation system was developed for use with the MSS CCT tapes. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment, in which several possible combinations of bands 5 and 7 and a contrast measure were tried, showed that an estimated gain in precision of 50% can be obtained in a multistage sampling design. The difference between bands 5 and 7 proved to be of special importance for the estimation of biomass in the form of timber volume. In addition, an interpretation model for high flight U2 photographs was developed. A maximum multiple correlation coefficient of 0.74 was obtained for the regression model, explaining 55% of the variation in timber volume as estimated from aerial photos and ground measurments. An interpretation model for MSS color composites is in the testing stage.

a Comprehensive Review of Pansharpening Algorithms for GÖKTÜRK-2 Satellite Images

NASA Astrophysics Data System (ADS)

Kahraman, S.; Ertürk, A.

2017-11-01

In this paper, a comprehensive review and performance evaluation of pansharpening algorithms for GÖKTÜRK-2 images is presented. GÖKTÜRK-2 is the first high resolution remote sensing satellite of Turkey which was designed and built in Turkey, by The Ministry of Defence, TUBITAK-UZAY and Turkish Aerospace Industry (TUSAŞ) collectively. GÖKTÜRK-2 was launched at 18th. December 2012 in Jinguan, China and provides 2.5 meter panchromatic (PAN) and 5 meter multispectral (MS) spatial resolution satellite images. In this study, a large number of pansharpening algorithms are implemented and evaluated for performance on multiple GÖKTÜRK-2 satellite images. Quality assessments are conducted both qualitatively through visual results and quantitatively using Root Mean Square Error (RMSE), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), Erreur Relative Globale Adimensionnelle de Synthése (ERGAS), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI).

Quantitative evaluation of multiple adulterants in roasted coffee by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) and chemometrics.

PubMed

Reis, Nádia; Franca, Adriana S; Oliveira, Leandro S

2013-10-15

The current study presents an application of Diffuse Reflectance Infrared Fourier Transform Spectroscopy for detection and quantification of fraudulent addition of commonly employed adulterants (spent coffee grounds, coffee husks, roasted corn and roasted barley) to roasted and ground coffee. Roasted coffee samples were intentionally blended with the adulterants (pure and mixed), with total adulteration levels ranging from 1% to 66% w/w. Partial Least Squares Regression (PLS) was used to relate the processed spectra to the mass fraction of adulterants and the model obtained provided reliable predictions of adulterations at levels as low as 1% w/w. A robust methodology was implemented that included the detection of outliers. High correlation coefficients (0.99 for calibration; 0.98 for validation) coupled with low degrees of error (1.23% for calibration; 2.67% for validation) confirmed that DRIFTS can be a valuable analytical tool for detection and quantification of adulteration in ground, roasted coffee. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of aroma enhancement for "Ecolly" dry white wines by mixed inoculation of selected Rhodotorula mucilaginosa and Saccharomyces cerevisiae.

PubMed

Wang, Xing-Chen; Li, Ai-Hua; Dizy, Marta; Ullah, Niamat; Sun, Wei-Xuan; Tao, Yong-Sheng

2017-08-01

To improve the aroma profile of Ecolly dry white wine, the simultaneous and sequential inoculations of selected Rhodotorula mucilaginosa and Saccharomyces cerevisiae were performed in wine making of this work. The two yeasts were mixed in various ratios for making the mixed inoculum. The amount of volatiles and aroma characteristics were determined the following year. Mixed fermentation improved both the varietal and fermentative aroma compound composition, especially that of (Z)-3-hexene-1-ol, nerol oxide, certain acetates and ethyls group compounds. Citrus, sweet fruit, acid fruit, berry, and floral aroma traits were enhanced by mixed fermentation; however, an animal note was introduced upon using higher amounts of R. mucilaginosa. Aroma traits were regressed with volatiles as observed by the partial least-square regression method. Analysis of correlation coefficients revealed that the aroma traits were the multiple interactions of volatile compounds, with the fermentative volatiles having more impact on aroma than varietal compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Determining particle size and water content by near-infrared spectroscopy in the granulation of naproxen sodium.

PubMed

Bär, David; Debus, Heiko; Brzenczek, Sina; Fischer, Wolfgang; Imming, Peter

2018-03-20

Near-infrared spectroscopy is frequently used by the pharmaceutical industry to monitor and optimize several production processes. In combination with chemometrics, a mathematical-statistical technique, the following advantages of near-infrared spectroscopy can be applied: It is a fast, non-destructive, non-invasive, and economical analytical method. One of the most advanced and popular chemometric technique is the partial least square algorithm with its best applicability in routine and its results. The required reference analytic enables the analysis of various parameters of interest, for example, moisture content, particle size, and many others. Parameters like the correlation coefficient, root mean square error of prediction, root mean square error of calibration, and root mean square error of validation have been used for evaluating the applicability and robustness of these analytical methods developed. This study deals with investigating a Naproxen Sodium granulation process using near-infrared spectroscopy and the development of water content and particle-size methods. For the water content method, one should consider a maximum water content of about 21% in the granulation process, which must be confirmed by the loss on drying. Further influences to be considered are the constantly changing product temperature, rising to about 54 °C, the creation of hydrated states of Naproxen Sodium when using a maximum of about 21% water content, and the large quantity of about 87% Naproxen Sodium in the formulation. It was considered to use a combination of these influences in developing the near-infrared spectroscopy method for the water content of Naproxen Sodium granules. The "Root Mean Square Error" was 0.25% for calibration dataset and 0.30% for the validation dataset, which was obtained after different stages of optimization by multiplicative scatter correction and the first derivative. Using laser diffraction, the granules have been analyzed for particle sizes and obtaining the summary sieve sizes of >63 μm and >100 μm. The following influences should be considered for application in routine production: constant changes in water content up to 21% and a product temperature up to 54 °C. The different stages of optimization result in a "Root Mean Square Error" of 2.54% for the calibration data set and 3.53% for the validation set by using the Kubelka-Munk conversion and first derivative for the near-infrared spectroscopy method for a particle size >63 μm. For the near-infrared spectroscopy method using a particle size >100 μm, the "Root Mean Square Error" was 3.47% for the calibration data set and 4.51% for the validation set, while using the same pre-treatments. - The robustness and suitability of this methodology has already been demonstrated by its recent successful implementation in a routine granulate production process. Copyright © 2018 Elsevier B.V. All rights reserved.

Fundamental Properties of the Red Square

NASA Astrophysics Data System (ADS)

Tuthill, Peter; Barnes, Peter; Cohen, Martin; Schmidt, Timothy

2007-04-01

This proposal follows the exciting recent discovery of the Red Square, the first near-sibling to the illustrious Red Rectangle; and also a potential example progenitor system for supernovae such as SN 1987A. Exploiting the unique extremely wide bandwidth correlator available at Mopra, we propose to rapidly and efficiently explore the molecular environment of this unique new object at 3 mm. This should reveal the fundamental properties of the gas in the underlying stellar system, and will provide the necessary springboard for future spatially-resolved work with interferometers.

Impact of Increasing Home Size on Energy Demand, The

EIA Publications

2012-01-01

Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator increases. Square footage typically stays fixed over the life of a home and it is a characteristic that is expensive, even impractical to alter to reduce energy consumption.

Forced-convection Heat Transfer to Water at High Pressures and Temperatures in the Nonboiling Region

NASA Technical Reports Server (NTRS)

Kaufman, S J; Henderson, R W

1951-01-01

Forced-convection heat-transfer data have been obtained for water flowing in an electrically heated tube of circular cross section at water pressures of 200 and 2000 pounds per square inch, and temperatures in the nonboiling region, for water velocities ranging between 5 and 25 feet per second. The results indicate that conventional correlations can be used to predict heat-transfer coefficients for water at pressures up to 2000 pounds per square inch and temperatures in the nonboiling region.

New infinite families of exact sums of squares formulas, Jacobi elliptic functions, and Ramanujan's tau function.

PubMed

Milne, S C

1996-12-24

In this paper, we give two infinite families of explicit exact formulas that generalize Jacobi's (1829) 4 and 8 squares identities to 4n(2) or 4n(n + 1) squares, respectively, without using cusp forms. Our 24 squares identity leads to a different formula for Ramanujan's tau function tau(n), when n is odd. These results arise in the setting of Jacobi elliptic functions, Jacobi continued fractions, Hankel or Turánian determinants, Fourier series, Lambert series, inclusion/exclusion, Laplace expansion formula for determinants, and Schur functions. We have also obtained many additional infinite families of identities in this same setting that are analogous to the eta-function identities in appendix I of Macdonald's work [Macdonald, I. G. (1972) Invent. Math. 15, 91-143]. A special case of our methods yields a proof of the two conjectured [Kac, V. G. and Wakimoto, M. (1994) in Progress in Mathematics, eds. Brylinski, J.-L., Brylinski, R., Guillemin, V. & Kac, V. (Birkhäuser Boston, Boston, MA), Vol. 123, pp. 415-456] identities involving representing a positive integer by sums of 4n(2) or 4n(n + 1) triangular numbers, respectively. Our 16 and 24 squares identities were originally obtained via multiple basic hypergeometric series, Gustafson's C(l) nonterminating (6)phi(5) summation theorem, and Andrews' basic hypergeometric series proof of Jacobi's 4 and 8 squares identities. We have (elsewhere) applied symmetry and Schur function techniques to this original approach to prove the existence of similar infinite families of sums of squares identities for n(2) or n(n + 1) squares, respectively. Our sums of more than 8 squares identities are not the same as the formulas of Mathews (1895), Glaisher (1907), Ramanujan (1916), Mordell (1917, 1919), Hardy (1918, 1920), Kac and Wakimoto, and many others.

Research on the Effects of Drying Temperature on Nitrogen Detection of Different Soil Types by Near Infrared Sensors.

PubMed

Nie, Pengcheng; Dong, Tao; He, Yong; Xiao, Shupei

2018-01-29

Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near infrared sensors are widely used for rapid detection of nutrients in soil. However, soil texture, soil moisture content and drying temperature all affect soil nitrogen detection using near infrared sensors. In order to investigate the effects of drying temperature on the nitrogen detection in black soil, loess and calcium soil, three kinds of soils were detected by near infrared sensors after 25 °C placement (ambient temperature), 50 °C drying (medium temperature), 80 °C drying (medium-high temperature) and 95 °C drying (high temperature). The successive projections algorithm based on multiple linear regression (SPA-MLR), partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were used to model and analyze the spectral information of different soil types. The predictive abilities were assessed using the prediction correlation coefficients (R P ), the root mean squared error of prediction (RMSEP), and the residual predictive deviation (RPD). The results showed that the loess (R P = 0.9721, RMSEP = 0.067 g/kg, RPD = 4.34) and calcium soil (R P = 0.9588, RMSEP = 0.094 g/kg, RPD = 3.89) obtained the best prediction accuracy after 95 °C drying. The detection results of black soil (R P = 0.9486, RMSEP = 0.22 g/kg, RPD = 2.82) after 80 °C drying were the optimum. In conclusion, drying temperature does have an obvious influence on the detection of soil nitrogen by near infrared sensors, and the suitable drying temperature for different soil types was of great significance in enhancing the detection accuracy.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

The Exponent of High-frequency Source Spectral Falloff and Contribution to Source Parameter Estimates

NASA Astrophysics Data System (ADS)

Kiuchi, R.; Mori, J. J.

2015-12-01

As a way to understand the characteristics of the earthquake source, studies of source parameters (such as radiated energy and stress drop) and their scaling are important. In order to estimate source parameters reliably, often we must use appropriate source spectrum models and the omega-square model is most frequently used. In this model, the spectrum is flat in lower frequencies and the falloff is proportional to the angular frequency squared. However, Some studies (e.g. Allmann and Shearer, 2009; Yagi et al., 2012) reported that the exponent of the high frequency falloff is other than -2. Therefore, in this study we estimate the source parameters using a spectral model for which the falloff exponent is not fixed. We analyze the mainshock and larger aftershocks of the 2008 Iwate-Miyagi Nairiku earthquake. Firstly, we calculate the P wave and SH wave spectra using empirical Green functions (EGF) to remove the path effect (such as attenuation) and site effect. For the EGF event, we select a smaller earthquake that is highly-correlated with the target event. In order to obtain the stable results, we calculate the spectral ratios using a multitaper spectrum analysis (Prieto et al., 2009). Then we take a geometric mean from multiple stations. Finally, using the obtained spectra ratios, we perform a grid search to determine the high frequency falloffs, as well as corner frequency of both of events. Our results indicate the high frequency falloff exponent is often less than 2.0. We do not observe any regional, focal mechanism, or depth dependencies for the falloff exponent. In addition, our estimated corner frequencies and falloff exponents are consistent between the P wave and SH wave analysis. In our presentation, we show differences in estimated source parameters using a fixed omega-square model and a model allowing variable high-frequency falloff.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

HBTprogs Version 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, D; Danielewicz, P

2002-03-15

This is the manual for a collection of programs that can be used to invert angled-averaged (i.e. one dimensional) two-particle correlation functions. This package consists of several programs that generate kernel matrices (basically the relative wavefunction of the pair, squared), programs that generate test correlation functions from test sources of various types and the program that actually inverts the data using the kernel matrix.

Spacing and shrub competition influence 20-year development of planted ponderosa pine

Treesearch

William W. Oliver

1990-01-01

Growth and stand development of ponderosa pine (Pinus ponderosa) were monitored for 20 years after planting at five different square spacings (6, 9, 12, 15, and 18 ft) in the presence or absence of competing shrubs on the westside Sierra Nevada. Mean tree size was positively correlated and stand values negatively correlated with spacing in the...

The correlation between albumin levels with 30 days mortality in community acquired pneumonia patients

NASA Astrophysics Data System (ADS)

Damayanti, N.; Abidin, A.; Keliat, E. N.

2018-03-01

The assessment of level severity ofCommunity-Acquired Pneumonia (CAP) patient at the early admission to the hospital is critical because it will determine the severity of the disease and the subsequent management of the plan. Albumin can be used as a biomarker to assess the severity of CAP. To identify the correlation between albumin level at early admission in hospital with 30-day mortality in patients with CAP. It was a cohort study. We had examined of 50 CAP subject with theCURB-65 score (Confusion, Urea, Respiratory rate, Blood pressure, Age >65years), albumin, sputum culture at the early admission at Emergency Room (ER). Then, albumin levels associated with 30-day mortality was assessed using Chi-Square test. Analysis with chi-square test found a significant correlation between albumin level with 30-day mortality (p=0.001) and Relative Risk was 2.376 (95% CI 1.515-3.723). It means that patients with CAP who has severe hypoalbuminemia have a higher risk ofdying in 30 days with 2,376 times more significant than patients with mild to moderate hypoalbuminemia. In conclusion, albumin levels at early admission in the hospital correlate with 30-day mortality in CAP patients.

Quantification of bone marrow fat content using iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): reproducibility, site variation and correlation with age and menopause.

PubMed

Aoki, Takatoshi; Yamaguchi, Shinpei; Kinoshita, Shunsuke; Hayashida, Yoshiko; Korogi, Yukunori

2016-09-01

To determine the reproducibility of the quantitative chemical shift-based water-fat separation method with a multiecho gradient echo sequence [iteraterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation sequence (IDEAL-IQ)] for assessing bone marrow fat fraction (FF); to evaluate variation of FF at different bone sites; and to investigate its association with age and menopause. 31 consecutive females who underwent pelvic iterative decomposition of water and fat with echo asymmetry and least-squares estimation at 3-T MRI were included in this study. Quantitative FF using IDEAL-IQ of four bone sites were analyzed. The coefficients of variance (CV) on each site were evaluated repeatedly 10 times to assess the reproducibility. Correlations between FF and age were evaluated on each site, and the FFs between pre- and post-menopausal groups were compared. The CV in the quantification of marrow FF ranged from 0.69% to 1.70%. A statistically significant correlation was established between the FF and the age in lumbar vertebral body, ilium and intertrochanteric region of the femur (p < 0.001). The average FF of post-menopausal females was significantly higher than that of pre-menopausal females in these sites (p < 0.05). In the greater trochanter of the femur, there was no significant correlation between FF and age. In vivo IDEAL-IQ would provide reliable quantification of bone marrow fat. IDEAL-IQ is simple to perform in a short time and may be practical for providing information on bone quality in clinical settings.

Lipidomics study of plasma phospholipid metabolism in early type 2 diabetes rats with ancient prescription Huang-Qi-San intervention by UPLC/Q-TOF-MS and correlation coefficient.

PubMed

Wu, Xia; Zhu, Jian-Cheng; Zhang, Yu; Li, Wei-Min; Rong, Xiang-Lu; Feng, Yi-Fan

2016-08-25

Potential impact of lipid research has been increasingly realized both in disease treatment and prevention. An effective metabolomics approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS) along with multivariate statistic analysis has been applied for investigating the dynamic change of plasma phospholipids compositions in early type 2 diabetic rats after the treatment of an ancient prescription of Chinese Medicine Huang-Qi-San. The exported UPLC/Q-TOF-MS data of plasma samples were subjected to SIMCA-P and processed by bioMark, mixOmics, Rcomdr packages with R software. A clear score plots of plasma sample groups, including normal control group (NC), model group (MC), positive medicine control group (Flu) and Huang-Qi-San group (HQS), were achieved by principal-components analysis (PCA), partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Biomarkers were screened out using student T test, principal component regression (PCR), partial least-squares regression (PLS) and important variable method (variable influence on projection, VIP). Structures of metabolites were identified and metabolic pathways were deduced by correlation coefficient. The relationship between compounds was explained by the correlation coefficient diagram, and the metabolic differences between similar compounds were illustrated. Based on KEGG database, the biological significances of identified biomarkers were described. The correlation coefficient was firstly applied to identify the structure and deduce the metabolic pathways of phospholipids metabolites, and the study provided a new methodological cue for further understanding the molecular mechanisms of metabolites in the process of regulating Huang-Qi-San for treating early type 2 diabetes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Field Performance of an Optimized Stack of YBCO Square “Annuli” for a Compact NMR Magnet

PubMed Central

Hahn, Seungyong; Voccio, John; Bermond, Stéphane; Park, Dong-Keun; Bascuñán, Juan; Kim, Seok-Beom; Masaru, Tomita; Iwasa, Yukikazu

2011-01-01

The spatial field homogeneity and time stability of a trapped field generated by a stack of YBCO square plates with a center hole (square “annuli”) was investigated. By optimizing stacking of magnetized square annuli, we aim to construct a compact NMR magnet. The stacked magnet consists of 750 thin YBCO plates, each 40-mm square and 80- μm thick with a 25-mm bore, and has a Ø10 mm room-temperature access for NMR measurement. To improve spatial field homogeneity of the 750-plate stack (YP750) a three-step optimization was performed: 1) statistical selection of best plates from supply plates; 2) field homogeneity measurement of multi-plate modules; and 3) optimal assembly of the modules to maximize field homogeneity. In this paper, we present analytical and experimental results of field homogeneity and temporal stability at 77 K, performed on YP750 and those of a hybrid stack, YPB750, in which two YBCO bulk annuli, each Ø46 mm and 16-mm thick with a 25-mm bore, are added to YP750, one at the top and the other at the bottom. PMID:22081753

Evaluation of fatty proportion in fatty liver using least squares method with constraints.

PubMed

Li, Xingsong; Deng, Yinhui; Yu, Jinhua; Wang, Yuanyuan; Shamdasani, Vijay

2014-01-01

Backscatter and attenuation parameters are not easily measured in clinical applications due to tissue inhomogeneity in the region of interest (ROI). A least squares method(LSM) that fits the echo signal power spectra from a ROI to a 3-parameter tissue model was used to get attenuation coefficient imaging in fatty liver. Since fat's attenuation value is higher than normal liver parenchyma, a reasonable threshold was chosen to evaluate the fatty proportion in fatty liver. Experimental results using clinical data of fatty liver illustrate that the least squares method can get accurate attenuation estimates. It is proved that the attenuation values have a positive correlation with the fatty proportion, which can be used to evaluate the syndrome of fatty liver.

Spectral L2/L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals

NASA Astrophysics Data System (ADS)

Wang, Dong

2018-05-01

Thanks to the great efforts made by Antoni (2006), spectral kurtosis has been recognized as a milestone for characterizing non-stationary signals, especially bearing fault signals. The main idea of spectral kurtosis is to use the fourth standardized moment, namely kurtosis, as a function of spectral frequency so as to indicate how repetitive transients caused by a bearing defect vary with frequency. Moreover, spectral kurtosis is defined based on an analytic bearing fault signal constructed from either a complex filter or Hilbert transform. On the other hand, another attractive work was reported by Borghesani et al. (2014) to mathematically reveal the relationship between the kurtosis of an analytical bearing fault signal and the square of the squared envelope spectrum of the analytical bearing fault signal for explaining spectral correlation for quantification of bearing fault signals. More interestingly, it was discovered that the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum corresponds to the raw 4th order moment. Inspired by the aforementioned works, in this paper, we mathematically show that: (1) spectral kurtosis can be decomposed into squared envelope and squared L2/L1 norm so that spectral kurtosis can be explained as spectral squared L2/L1 norm; (2) spectral L2/L1 norm is formally defined for characterizing bearing fault signals and its two geometrical explanations are made; (3) spectral L2/L1 norm is proportional to the square root of the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum; (4) some extensions of spectral L2/L1 norm for characterizing bearing fault signals are pointed out.